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Investigating school finance adequacy in the San Marino Unified School District

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Investigating school finance adequacy in the San Marino Unified School District

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Investigating School Finance Adequacy in the San Marino Unified School District
by
Ryan Steven Kachold

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

May, 2021

© Copyright by Ryan Steven Kachold 2021
All Rights Reserved

The Committee for Ryan Steven Kachold certifies the approval of this Dissertation

Larry Hausner
Adam Kho
Larry Picus, Committee Chair

Rossier School of Education
University of Southern California
2021

iv

Abstract
This study explores the topic of school finance adequacy by looking at a small, public school
district located in San Marino, California. More specifically, the researcher applies one of the
four known methods of determining adequacy, the Evidence-Based model, to the district’s
current allocation of resources. The researcher inputs a variety of accounting and human
resources data points into the Evidence-Based model to generate a side by side comparison of the
Evidence-Based model’s suggested resource levels and the district’s current levels of resource
allocation. The study also examines the nature of how local revenues outside of the state funding
formula are used in the district to achieve more adequate levels of funding for the schools. This
quantitative analysis allows the researcher to further understand not only the extent to which the
district provides an adequate education to its students, but also the implications other locally
generated revenues have on the district’s overall resource landscape. The findings indicate that
the district faces an overall resource gap, according to the Evidence-Based model of school
finance adequacy. The gap is largest in the area of core teachers. Moreover, findings indicate that
the district relies very heavily on other locally generated revenues to function in its current state.
The Evidence-Based model results indicate that the district does have some ability to reallocate
certain funds in different areas to move closer to providing an adequate education for its
students.

v

Dedication
To my mom, who has always used love and high expectations to push me to be better, work
harder, and pursue the next opportunity.

vi

Acknowledgements
Thank you to all the friends and colleagues who encouraged me to pursue this degree.
Without your help and support, the journey would have been much more difficult. I want to also
give a special thanks to the accounting personnel in the San Marino Unified School District
central office for their responsiveness and willingness to provide the data and information
needed to conduct both a rigorous and high-quality analysis. Thank you also to my dissertation
committee for their patience, criticism, and for volunteering for their roles in this process for me.
Lastly, I would like to thank Dr. Picus for providing me with a truly engaging glimpse into the
world of school finance and resource allocation. It has been satiating for my intellect and
lucrative in my professional context.
As an assistant principal in the San Marino Unified School District, I want to
acknowledge my loyalty and dedication to the mission of the district, but also my passion and
dedication to understanding the policy and larger, social impact and workings of school finance
and resource allocation on the children who attend and adults who work in the field. I have made
every objective attempt throughout this work to acknowledge larger truths and objective realities
facing trends in public education as well as the San Marino Unified School District itself.

vii

Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. ix
List of Abbreviations ...................................................................................................................... x
Chapter One: Overview of the Study .............................................................................................. 1
Introduction ......................................................................................................................... 1
Measure E Parcel Tax Failure ............................................................................................. 2
School Finance General Context ........................................................................................ 3
Statement of the Problem .................................................................................................... 7
Purpose of the Study ......................................................................................................... 13
Significance of the Study .................................................................................................. 15
Definitions......................................................................................................................... 17
Chapter Two: Literature Review .................................................................................................. 21
Introduction ....................................................................................................................... 21
Impact of Litigation on Development of School Finance ................................................. 21
Taxpayer Equity ................................................................................................................ 27
Does Money even Matter? ................................................................................................ 28
Adequacy .......................................................................................................................... 30
Chapter Three: Methodology ........................................................................................................ 54
Research Questions ........................................................................................................... 55
Sample and Population ..................................................................................................... 55

viii

Overview of the District.................................................................................................... 56
Instrumentation and Data Collection ................................................................................ 58
Data Analysis .................................................................................................................... 60
Chapter Four: The Findings .......................................................................................................... 62
Introduction of the Findings.............................................................................................. 62
Overview of the San Marino Unified School District ...................................................... 63
Breakdown of Revenue Sources by FTE for the SMUSD ................................................ 66
Evidence-Based Model Outputs for the SMUSD ............................................................. 69
District Office ................................................................................................................... 96
Maintenance and Operations............................................................................................. 97
Food Services .................................................................................................................. 100
Impact of COVID-19 ...................................................................................................... 100
Conclusion ...................................................................................................................... 102
Chapter Five: Summary, Conclusions, and Implications............................................................ 104
Purpose of the Study ....................................................................................................... 104
Summary of the Findings ................................................................................................ 105
Limitations of the Study.................................................................................................. 109
Policy Implications ......................................................................................................... 115
Concluding Comments.................................................................................................... 119
References ................................................................................................................................... 121

ix

List of Tables
Table 1 2018 Source of Revenues for Public Elementary and Secondary Education..................... 9
Table 2 Summary of State Adequacy Studies, 2003-2014 ............................................................ 32
Table 3 Summary of Montana PJ Panel Recommendations for PPE ........................................... 38
Table 4 2016 Evidence-Based Model Elements and Formula Recommendations ....................... 40
Table 5 2018-2019 SMUSD Demographics ................................................................................. 57
Table 6 2018-2022 SMUSD LCFF PPEs, Key Expenditures and Revenue Assumptions ........... 65
Table 7 2020-2021 SMUSD Certificated FTE by Revenue Source ............................................. 67
Table 8 2020-2021 SMUSD Certificated FTE by Revenue Source as Percentages ..................... 68
Table 9 Evidence-Based Model Gap Analysis for Total SMUSD Revenue and FTE .................. 71
Table 10 2020-2021 Certificated SMUSD FTE by Revenue Source............................................ 80
Table 11 Evidence-Based Model Gap Analysis for High School FTE and Total Revenue .......... 81
Table 12 2020-2021 Certificated High School FTE by Revenue Source ..................................... 84
Table 13 Evidence-Based Model Gap Analysis for Middle School FTE and Total Revenue....... 85
Table 14 2020-2021 Certificated Middle School FTE by Revenue Source .................................. 88
Table 15 Evidence-Based Model Gap Analysis for Elementary School FTE and Total Revenue 89
Table 16 2020-2021 Certificated Elementary School FTE by Revenue Source ........................... 92
Table 17 SMUSD Allocation and EB Model Recommendation for Dollar Resources ................ 94
Table 18 SMUSD Allocation and EB Model Recommendation for Central Office Staffing ....... 96
Table 19 SMUSD Allocation and EB Model Recommendation for Custodial Staffing ............... 97
Table 20 SMUSD Allocation and EB Model Recommendation for Groundskeeper Staffing ...... 98
Table 21 SMUSD Allocation and EB Model Recommendation for Maintenance Staffing .......... 99
Table 22 Total FTE Comparison by Revenue Source with Overall EB Model Revenue Gap.... 107

x

List of Abbreviations
CCSS Common Core State Standards

CF Cost Function

EB Evidence-Based

FTE Full Time Equivalent

LCFF Local Control Funding Formula

PJ Professional Judgment

PPE Per Pupil Expenditure

SMSF San Marino Schools Foundation

SMUSD San Marino Unified School District

SPED Special Education

SSD Successful Schools/District

VAPA Visual and Performing Arts
1

Chapter One: Overview of the Study
Introduction
One of the fundamental challenges embedded in the field of public education revolves
around the discovery of systematic structures to improve student achievement across contexts. In
the past, funding and resource allocation has been heavily investigated for its applicability and
role in the creation of such structures. Odden and Picus (2020) have identified and provided a
few of these structures, namely setting ambitious goals, being strategic about core and elective
classes, engaging in data-based decision-making, and providing extra help for struggling
students. The historical and fundamental nature of public school financing continues to be
complex and varied both within and across states, making it more difficult to systematically
operationalize it for the purposes of improving student achievement, regardless of context.
One important component of school finance is the idea of adequacy, which will function
as the central concept under study here, and is defined simply as an environment where every
child that is part of the system receives the educational resources needed plus extra, if
appropriate, to reach the level of quality outlined, in many cases, by the level of education
prescribed in a state’s constitution or adopted performance standards (Odden & Picus, 2020).
Districts that are adequately funded, furthermore, receive the amount of financial resources
necessary to facilitate the creation of that environment (Odden & Picus, 2020). Any term
attached to the word adequacy in this study specifically entails a level at which a particular
educational organization not only is funded in the manner described above, but also has the
ability to create an environment using those resources to allow each student the opportunity to
meet performance standards.
2

Measure E Parcel Tax Failure
Throughout the study, I refer to parcel taxes as a critical source of local revenue for the
San Marino Unified School District (SMUSD). The larger of these two parcel taxes, Measure E,
underwent a renewal election shortly after the completion of the data analysis and the presenting
of the findings for the study and failed to secure a two-thirds majority vote to renew the parcel
tax. This parcel tax provides just over $4 million in revenue primarily directed at reducing class
size and funding specialized elective programs for the SMUSD. This translates into a full time
equivalent (FTE) staffing cut of approximately 30 FTE for the district, critically impacting the
SMUSD’s ability to deliver resource adequacy to its students as defined by the Evidence-Based
(EB) model of school finance adequacy.
The SMUSD is likely to put Measure E on the ballot for the August special election.
However, by this point the district will have already delivered layoffs to over 30 employees. A
successful renewal will require a formal rehiring process for the district as final layoff notices
will have been delivered by May 2021. The failure of this local revenue source to continue
results in a 35% teacher reduction at both the middle and high school. This parcel tax provides
the most significant source of local revenue for the district, which means its failure realizes a
serious cliff for the district’s resources. According to the findings presented below, the district is
already experiencing an adequacy gap. Without this revenue, the district faces a critical blow to
its resources.
In the immediate future, SMUSD leadership is exploring its options, including engaging
the board of education in a long term strategic planning process, potential school closure,
integration of the middle and high school, an aggressive campaign to raise funds by the San
Marino Schools Foundation (SMSF) and other solutions. One of the fundamental tensions
3

presented in this study revolves around the way resources might affect students’ academic
performance in an affluent community like San Marino. The SMUSD has a longstanding
tradition of academic excellence, however, it has always been heavily supported financially by
the community. Whether or not the failure of this parcel tax will impact student achievement is
yet to be seen, however, it delivers a significant blow to the school district’s resources, and
dramatically increases the gaps presented in chapter four of this study.
The data analysis, findings, implications, and recommendations presented in chapters
four and five of this study reflect the resource landscape of the district prior to the failure of the
parcel tax. In summary, the gaps presented below will now be heavily exacerbated, with even
larger gaps now affecting the district, mostly in the core content area and specialist or elective
teacher positions as these positions were directly tied to the resources provided by Measure E.
While performance has traditionally indicated the presence of an adequate education for its
students, the financial landscape will now reflect a dramatic distance from adequacy as measured
by the Evidence-Based (EB) model of school finance adequacy.
School Finance General Context
In an account of the school finance context, Springer, Houck, and Guthrie (2015) cited
two critical elements that impact the general understanding and policy implications of school
finance. The first is the steadily growing financial investment into public education by the United
States, at both the state and federal level. While the federal investment has gone from roughly
nothing in the early 1900s to about 10% of total PK-12 educational expenditures as of 2009, state
contributions have risen from a little less than 20% in the early 1900s to over 50% as of 2009
(Springer et al., 2015; Gordon, 2015). The federal government’s response to the Great Recession
in 2009 came in the form of the American Recovery and Reinvestment Act (ARRA), which
4

temporarily increased federal investment to 111% more than the level of federal funding present
during 2000-01, an increase from $42 billion to $89 billion (Hussar et al., 2020). Federal
revenues have decreased by 33% since 2009-10, back to contributing 8% of total revenues in
2016-17 (Hussar et al., 2020). Furthermore, the Coronavirus Aid, Relief, and Economic Security
Act (CARES), another federal response, but to the COVID-19 pandemic of 2020, proposes
another large share of federal revenues available through September of 2021 (Skinner et al.,
2020). Specifically, the Elementary and Secondary School Emergency Relief (ESSER) portion
of the CARES act provides a figure of $13.2 billion (Skinner et al., 2020), while the entire
CARES act is set to provide K12 education with approximately $200 billion. This has been a
result of increasing demands on the field of public education to produce improved results, moves
to raise investment in the high human capital demand of the profession, attempts to equalize
wealth across school districts, and intervene during times of economic distress (Springer et al.,
2015; Odden & Picus, 2020).
This increase in investment has ultimately shown an increase in average per pupil
expenditures (PPE) from approximately $2,000 in 1950 to $14,439 in 2016-17 (Springer et al.;
Hussar et al., 2020). The increased investment over time into education in the United States
reflects the growing measures of accountability that have also risen. This idea contributes, in
part, to the concept of school finance adequacy.
The second element mentioned by Springer et al. (2015) centers on the movement of
labor. The authors explain that many industries, such as agriculture, manufacturing,
transportation, communication, and finance have become increasingly capital intensive, relying
less on the amount and quality of labor coming into the workforce. Education, according to these
authors, has moved in the opposite direction, requiring more labor than other industries as time
5

has gone on. More importantly, education has not only required more labor, but a higher quality
of labor to match the increased expectations and accountability measures that have come from
the federal and state policymaking bodies. Hussar et al. (2015) showed the pupil-teacher ratio to
be 16:1 in 2016, decreasing from 25:1 in 1955. Furthermore, the authors say most teachers had
an average of 15 years of experience in 1987, with teachers having just an average teaching
experience of 5 years in the 2011-12 school year. While the need for more, higher quality labor
has increased, this research suggests a “greening” of the education workforce (Ingersoll et al., p.
11, 2014). This explains the greater investment into public education, specifically instruction
costs, by state governments.
The school finance context covers a notable amount of the overall economic landscape in
the United States (Odden & Picus, 2020). Snyder et al. (2019) showed that during 2017, all
elementary and secondary schools revenues were more than $789 billion and consumed 4
percent of the gross domestic product. Odden and Picus (2020) concluded their overview by
noting the disparities in spending within and across public school districts and states. Because
public school is, in large part, funded by local property taxes, more wealthy and affluent districts
have historically been able to spend more at an equal tax rate than lower value areas (Odden &
Picus, 2020). Although the states have drastically increased their role in providing resources to
school districts, these spending disparities continue to exist. Moreover, Ingersoll et al.’s (2014)
research suggested that the greater inexperience that exists in the workforce tends to be funneled
to the property poor areas, as they cannot afford to spend as much on the high-quality labor
mentioned by Springer et al. (2015).
Another essential element of the school finance context are the reform efforts of the past
two decades. Corcoran and Evans (2015) explained that a reason for the increased state
6

responsibility comes from court ordered and legislative reforms. School finance reform efforts
began first as a challenge to reduce disparities in PPE that occurred as a result of differences in
local property tax wealth. Plaintiffs found minimal success when they attempted to litigate using
the equal protection clause in the United States Constitution. These reform efforts evolved into
state by state affairs that not only sought to bring more equitable spending into school finance
structures through state constitutions, but more recently a push to achieve adequate spending.
More specifically, reform efforts are targeted at understanding the level of resources needed for
all students to achieve established standards of success and finding solutions to bring the needed
resources to schools. Corcoran and Evans (2015) pointed out that this centralization of school
spending to the state level is in its infancy and that minimal evidence exists to inform researchers
and practitioners of the effects of this centralization in the long run. However, the authors did
point out that the centralization has led to increased accountability measures that are attached to
the resources.
The centralization of school finance efforts has also made its way to the federal level.
While federal dollars have typically averaged only 10% of the overall revenue stream in recent
decades, nearly all of these resources are designed to support vulnerable student populations
(Springer et al., 2015; Gordon, 2015). The No Child Left Behind Act (NCLB) reauthorized the
Elementary and Secondary Education Act (ESEA), which brought increased accountability and
structure to the accessibility of the funds. For states to access these federal funds, they need to
show adequate yearly progress (AYP) toward their respective state’s established performance
standards, particularly for identified student subgroups, such as socioeconomically
disadvantaged and foster student groups. Gordon (2015) suggested that this type of policy has
drastically changed the way education looks at the classroom level. Schools, with increased
7

accountability measures at the state and federal level, spend significantly more time teaching
reading and math and more time redesigning curricula to align with state established
performance and content standards (Jennings & Rentner, 2006).
The school finance context has largely been characterized by a shift from a strong local
influence to a centralization at the state level. It must be noted, however, that while an emphasis
on equity and adequacy has developed, in addition to a use of performance standards, there are
still substantial funding inequities in many states. At the heart of the funding system of schools is
the local property tax base. A combination of policy and court driven reform has attempted to
offset the local property tax influence to provide equitable, and more recently, adequate levels of
education according to each respective state’s education clause.
Statement of the Problem
The National Research Council (1999) described the education system in the United
States as characterized by large disparities within and across local schools, school districts and
states. These disparities often cause a lack of equal opportunity (Rubenstein, 2016), especially
for students in property poor areas. Property poor areas tend to serve students that require greater
resources while locales with sturdier and larger property tax bases tend to serve students who
have more social opportunity and require less intensive financial resources (National Research
Council, 1999). Local property tax bases provide a significant source of funding for public
education systems with state governments assuming more of the burden as time has gone on as a
result of school finance reform efforts taking place largely through the state court systems. Much
of these reform efforts are driven by the idea of fiscal neutrality (Coons et al., 1970; Wise, 1968),
or the idea that property wealth per pupil, or expenditure per pupil, should not be a measure of a
particular area's property wealth (National Research Council, 1999). Essentially, a widespread
8

belief that disparities in funding and spending were inequitable began to transform into lawsuits
and eventual reform efforts.
The National Center for Education Statistics (NCES) (2018) published a report on
revenues and expenditures that gives quantitative substance to the problem described above. This
report sheds further light on how vastly unequal spending is not only based on how much local,
state, and federal resources each particular state receives, but also how vastly different PPE are
from state to state. Table 1 shows a few key states and their local, state, and federal revenue
sources. While the NCES table lists all states, only a few were selected to represent in Table 1.
The table was also adapted to display a breakdown by percentage of local, state, and federal
revenues. Table 1 clearly displays how differently some states can resource their primary and
secondary education systems.

9

Table 1
2018 Source of Revenues for Public Elementary and Secondary Education
State
California
New
Jersey Vermont New York Utah
New
Hampshire
Total
Revenues (in
thousands of
dollars) ($)
85,779,627 29,671,607 1,724,527 65,776,757 5,447,070 3,055,956
Revenues Per
Pupil ($)
11,420 19,041 19,023 22,231 7,006 15,535
Percent of Total by Source (%)
Local 32.1 53.1 4.1 53.2 37 61.4
State 59.4 42.7 89.3 41.7 54.6 32.9
Federal 8.5 4.2 6.6 5 8.3 5.7

Note. Adapted from the National Center for Education Statistics. (2018). Revenues and
Expenditures for Public Elementary and Secondary Education: School Year 2015–16 (Fiscal
Year 2016). Washington, DC: Department of Education.
https://nces.ed.gov/pubs2019/2019301.pdf. Copyright 2018 by the National Center for Education
Statistics

At one point, all of these states funded education systems almost entirely through local
sources. Various reform efforts through policymaking and court rulings have led each state to
alter their individual systems of resource allocation for schools. In California, for example, the
Serrano v. Priest (CA) court case tremendously changed the landscape of school finance over
time. In addition to Legislative reforms in response to the Serrano rulings California’s voters
passed Proposition 13 in 1978, limiting the property tax rate and assessed value as well as
limiting the ability to raise taxes in the future. As a result, California relies more on state than
local revenues to support public schools.
10

Vermont differs from most other states. Responding to a court ruling in Brigham v. State
in 1997, Vermont passed Act 60, which as amended several times has come close to achieving
the concept of fiscal neutrality (Coons et al., 1970; Wise, 1968) and equal opportunity
(Rubenstein, 2016). New Jersey has had a long running legal battle over creating a more
equitable and adequate school finance system. The Abbot v. Burke (NJ) cases are well known
and referenced for representing a true evolution from fiscal neutrality to adequacy (Odden &
Picus, 2020). As seen in Table 1, however, most of the New Jersey school district revenue still
comes from local sources, unlike Vermont and California.
Widely different makeups of local, state, and federal revenues occur across the nation,
but the more concerning metric, which also varies from state to state or even district to district,
are PPE. When the figure of PPE is disparate, it largely contributes to the vastly different
resource levels and directly impacts students and schools. The NCES (2018) report also
showcases this data. Table 1 showcases PPE and has been adapted from the original table which
shows all 50 states. Six particular states have been chosen to showcase the large disparities in
PPE from state to state. New York spends the most per pupil in the entire United States.
However, within New York, massive disparities exist. Some areas in New York spend twice as
much as in others (National Research Council, 1999). Utah lies at the lowest PPE of any state,
while California is in the bottom 25%. Ultimately, much of the disparities that exist are due, in
part, to the amount of influence local property tax revenues hold. However, in cases like
Vermont, whose PPE is $19,023, near New York, the local property tax influence has been
subverted in large part due to attempts to achieve more equitable and adequate funding structures
through litigation efforts and reform. As it is clear that PPE and revenues differ vastly from state
to state, and even district to district or school to school, the problem becomes one of determining
11

how much money a high-quality education costs, according to each respective state’s education
clause. States can have vastly different percentages of local, state, and federal revenue supporting
their public education system, but the variable that ultimately impacts the quality of education
students receive is, mostly, PPE.
As reformers and policymaking bodies have begun to focus efforts on reducing
disparities in funding, the concept of school finance adequacy has gained more presence in both
the legal and educational finance context as a way to measure both appropriate funding levels
and equity across school districts within a state. There are four different models of school finance
adequacy in the current literature. The first is the Professional Judgment method which relies on
experts in the field to produce a model or formula by which to resource schools. The second is
the Cost Function model, which relies entirely on statistical analysis to determine adequate
funding levels, particularly for PPE at the school level. The third, the Successful Schools model,
attempts to recreate resource allocation structures in a given school or district based on similar
organizations that have achieved recognizable success. The last and final model, which will be
applied in this study, is the Evidence-Based (EB) model, which incorporates elements of the
Professional Judgment model, but uniquely incorporates a synthesis of empirical, educational
research principles. All four of these models attempt to solve the problem of inequitable and
disparate funding within and across state educational systems by offering a model that informs
an education organization of the degree to which their schools and students are being resourced
adequately. The EB model also provides a theory of action to identify educational organization
and process that will ideally lead to improved student performance.
The present study uses the EB model to inform one particular school district, the San
Marino Unified School District (SMUSD), of the nature to which they are providing an adequate
12

education for their students. It should be noted, however, that as the study progresses, additional
elements of revenue will be referenced, including contributions from the San Marino Schools
Foundation (SMSF) and the revenue from two district parcel taxes. These revenue streams for
the SMUSD lie outside of the Local Control Funding Formula (LCFF). As revenue sources
generated entirely by the community, they can also provide great insight into the priorities of the
local community and their significance is important to understanding how resources are allocated
in San Marino and in measuring the level of adequacy that exists in the SMUSD. The results of
the EB model analysis will shed further light on how not only the LCFF funds are used, but also
how the SMSF and parcel tax revenues provide SMUSD students with an adequate education.
San Marino Schools Foundation (SMSF)
The SMSF is a unique organization that exists alongside the SMUSD to raise funds to be
used by the school district. The organization was founded in 1980 and has provided over 48
million dollars to the SMUSD over the course of its lifetime (San Marino Schools Foundation).
The organization prides itself on being an immensely significant bridge between the community
and the school district (San Marino Schools Foundation). Furthermore, the SMSF attributes
much of the community’s prestige and civic reputation to the quality of its public schools (San
Marino Schools Foundation). Students in the SMUSD are competing for college and life
opportunities with the highest caliber of students around the world and the SMSF aims to
reliably resource the SMUSD public schools to allow its students to continue to compete in this
arena (San Marino Schools Foundation). One of the closing points the organization’s website
makes relates specifically to this study. The organization cites a lack of funding from the
government which the SMSF must make up (San Marino Schools Foundation). Note that the
SMUSD receives less funding per pupil than most other districts, relatively, through the LCFF
13

and its specific funding formula. The SMUSD enrolls virtually no students from at-risk
backgrounds, which means it does not generate any supplemental or concentration grant funding
from the state’s LCFF formula. The LCFF specifically provides additional financial resources to
school districts with larger amounts of at-risk student populations.
Parcel Taxes: Measures E and R
In addition to the SMSF, the district maintains two parcel taxes: Measures E and R.
These two parcel taxes combined provide almost six million dollars annually to the school
district. This revenue is locally generated tax revenue, whereas the SMSF is comprised entirely
of donations from the community. These parcel taxes generate revenue specifically for the school
district, whereas general (Proposition 13) local property taxes are collected for a variety of
purposes, including public schools. Measure R has been in place since 1991 and is renewed
every six years. Measure E has been in place since 2009 and is also up for renewal by vote every
six years. These parcel taxes, along with the foundation, provide resources mostly in the form of
people at each of the four schools in the SMUSD.
Research Questions
RQ 1: What resource allocation gaps does the Evidence-Based model of school finance adequacy
estimate for the San Marino Unified School District (SMUSD)?
RQ 2: What are the implications of these findings for the allocation and use of both LCFF and
other locally generated resources in the San Marino Unified School District?
Purpose of the Study
The EB model has been proven influential in designing a structure that articulates
adequate funding at nearly all levels of the K12 educational context (Odden, Picus, & Goetz,
2010). Using a combination of empirical research around student achievement and professional
14

judgment panels, the EB model creates a tool for decision-making that outlines the amount and
target of resources required for a specific context to achieve adequate per pupil spending and
allocation of resources. The vast number of federal and local court cases show local funding
formulas to fall short of providing students with an adequate education. The standards-based,
testing accountability elements of NCLB, determining adequate resources at a specific level, for
a specific context has become both significant and essential (Odden, Picus, & Goetz, 2010).
The SMUSD is a wealthy district located in the Pasadena area of California. More
specifically, the district is located in the small city of San Marino. The 2018 median household
income was $152,527 compared to $61,015 in Los Angeles County (SCAG, 2019). The median
home sales price was $2,117,500 compared to $597,500 in Los Angeles County (SCAG, 2019).
In terms of LCFF resources, the district receives a small amount relative to the socioeconomic
characteristics of the community. This makes SMUSD an interesting organization to study under
the focus of school finance adequacy. Historically, affluent areas receive greater funding as a
result of higher local property tax wealth. The LCFF system in California, however, is designed
to divert more resources to student populations identified as either at-risk or disadvantaged. The
SMUSD enrolls virtually no students who qualify for the supplemental state resources. The
combination of the very small size of the SMUSD at roughly 3,000 students with the fact that it
receives virtually no supplemental resources for identified student groups makes the overall PPE
in SMUSD low relative to its local property value.
The relatively low PPE in SMUSD has been offset by the foundation which is run and
organized by the community in addition to the two parcel taxes which help to supplement the per
pupil funding provided by the LCFF. The combination of LCFF, SMSF, and parcel tax resources
allows the SMUSD to resource its students similar to other wealthy, much larger districts such as
15

Beverly Hills Unified or Palos Verdes Unified. The purpose of the study then, is to use the EB
model to first determine whether or not and to what extent the SMUSD provides its students with
an adequate education based on the LCFF resources. More significantly, however, are
implications of the findings for how the district allocates the money generated by the SMSF and
parcel taxes. The EB model may provide the SMUSD with a fresh perspective related to its use
of both LCFF and non-LCFF resources that may lead to more effectively allocating them at each
of the four schools in the district.
Significance of the Study
The school district in San Marino continues to have a significantly involved community,
due in large part to the resources generated by the SMSF and parcel taxes. Parents and
community members who actively donate to the foundation have stronger voices with much
greater leverage for decision-making. In 2020, the district is experiencing somewhat of a
financial hardship, cutting many district and even site positions, including not backfilling the
retirement of an assistant superintendent. This study could provide the SMUSD and its
community with decision-making leverage to improve the allocation of resources for its schools
and students. While the district is small and experiencing financial hardship, it also suffers from
declining enrollment as a result of the prestigious private schools nearby. Parents in the
community have the resources to send their children to these schools when they feel that the
public district is not providing the service they expect. The EB model has been used in dozens of
states from the school level to the state legislature. Given the fact that the district has not
undergone an adequacy study before, this opportunity could prove significant in reshaping the
effectiveness of the resources available to the district.
16

According to the California School Dashboard (2017), SMUSD students perform at or, in
some cases, far above the standard for ELA and math. In some ways, this demonstrates that
students are, to some degree, being provided with an adequate education based on test scores. It
is critical to consider, however, that while students are performing on state standardized tests in a
way that reflects the receiving of an adequate education, the current allocation of resources may
suggest a surplus or gap, according to the EB model’s outputs. Moreover, the academic
performance may indicate a standard of adequacy, but the resource levels may not. It is unlikely
that the district’s LCFF allocation alone will meet the EB model’s level of resourcing, however,
the addition of the other locally generated revenues may fill the gap, further justifying the high
academic student performance in the district.
Another element of significance as it relates to this study has to do with the phenomenon
of declining enrollment. The SMUSD lies, geographically, in a pocket of highly competitive and
prestigious private institutions. The community wishes to remain competitive in this market, and
the schools foundation and parcel taxes have provided some level of interference with the
declining enrollment of the district in recent years, although there is still evidence of it in the
district. This study can organize and illuminate some of the ways in which the SMUSD uniquely
incorporates other locally generated revenues to remain competitive with local, private
educational institutions. Without the use of these other locally generated revenues, the SMUSD
might face much steeper, more rapid levels of declining enrollment. The EB model of school
finance adequacy will help to explain how these additional resources manifest at the school level
in terms of human resources and other instruction-related costs.
17

Definitions
Accountability: The principle that a given individual or organization is responsible to produce
established outcomes
Adequacy: The provision of sufficient per pupil funding and effective resource allocation that
provides all students in a given school or district the opportunity to achieve at a respective state’s
education standards
Common Core State Standards (CCSS): The state of California’s established educational
performance standards
Cost function: One of four adequacy approaches that relies entirely on statistical principles and
mathematical calculations
Education clause: A clause in a state’s constitution that defines parameters for the role of public
education
Educational need concept: Concept devised by (Coons et al., 1970; Wise, 1968) that claims the
judicial test of strict scrutiny should always apply in the case of education funding systems over
rational basis
Equal protection clause: The act of governing that does not differentiate the protection of certain
groups based on individual characteristics
Equity: The concept that students are unique and require different levels of resources to access
opportunities and achieve academic success
Evidence-Based model: One of four adequacy approaches that incorporates educational research
and the expertise of professionals in the field of education
Fiscal neutrality: The concept that a given locales property wealth should not determine the
quality of education a child receives from the public education system
18

Fundamental right: The notion that education aligns with other fundamental rights such as life,
liberty, and the pursuit of happiness
Gap analysis: The act of determining the goal of an organization and where it currently lacks in
relation to the goal, specifically around knowledge, motivation, and organizational factors (Clark
& Estes, 2008)
Horizontal equity: The concept that students with identical demographics in equal situations
receive the same amount of resources
Litigation: The process of taking formal legal action
Local control: The concept that control over the educational system historically lies at the local
level and strongly aligns with the precedent of local property taxes funding public education
Local Control Funding Formula (LCFF): California’s method for determining per pupil funding
for public school districts that takes into account student characteristics
Multi-tiered systems of support (MTSS): A framework that separates groups of students or people
into three different tiers, each requiring a different level of support and intervention to optimize
chances for success
Parcel tax: A separate tax bill for any piece of land that lies wholly or partially within the
boundaries of the San Marino Unified School District where the entire tax goes directly to the
school district
Per pupil weighting formula: A method of determining how much money a student receives,
usually operationalized at the state level
Professional judgement: One of four adequacy approaches that relies entirely on the expertise of
professionals to determine adequacy for a given school, district, or state
19

Professional learning community (PLC): A research-based professional development paradigm
that emphasizes teacher collaboration, data-based decision making, and reflection
Rational basis: The more favorable judicial test for state legislatures that relies only on providing
a rational argument for the nature of a state’s education funding system
Reform: The process of enacting change to improve a social, political, or economic condition in
a given context
Resource allocation: The process of dispersing financial resources to or for specific programs,
personnel costs, or materials at the school or district level
San Marino Schools Foundation: A non-profit organization founded in 1980 to provide financial
support to the San Marino Unified School District
School finance: The study of how public schools are funded
School finance adequacy model: The process by which consultants or experts determine how to
move a state, district, or school closer toward providing an adequate education for their students
State and federal policymaking: The act of decision-making or formulating accountability
measures at the state and federal levels
Strict scrutiny: A judicial test that requires the state legislature to prove that a model for funding
schools exists in pursuit of a compelling interest, that it is not overly broad, and that there is no
less discriminatory means possible to achieve the goal of the law (Odden & Picus, 2020)
Successful schools/district: One of four adequacy approaches that relies on the examination of
similar schools or districts to determine one’s own model for amount and allocation of resources
Teacher experience: The amount of years and formal training a teacher possesses
Vertical equity: The idea that certain students require more resources than others to access
experiences and achieve favorable educational outcomes
20

Following this introductory chapter, chapter two lays out a literature review of the
concept and development of school finance adequacy. Some of the key literature explores the
history of school finance litigation, the concept of taxpayer equity, as well as the polarizing
debate over the extent to which educational research has been able to correlate a level of
resources with broad increases in student achievement. Chapter three describes the methodology
of the study as a quantitative analysis, with information and further explanation of data analysis
procedures, as well a description of the population and sample for the study. Chapter four
discusses the findings of the study and the remaining chapter outlines a summary of the findings,
limitations of the study, as well as implications for the study and policy recommendations for the
San Marino Unified School District.

21

Chapter Two: Literature Review
Introduction
An application of the Evidence-Based (EB) school finance adequacy model requires a
review of existing literature that covers four primary areas: the impact of litigation on the
development of the concept of adequacy, the existing variable of taxpayer equity, the scholarly
debate around whether or not money matters, and ultimately an explanation and discussion as to
how adequacy studies are performed. A few other areas are also mentioned for their relevance
and role in the study. California’s Common Core State Standards (CCSS) are addressed as well
as reference to the gap analysis methodology. Lastly, literature around nontax revenues is briefly
mentioned as the context in focus utilizes a source of revenue generation from a nontax revenue
source.
Impact of Litigation on Development of School Finance
Odden and Picus (2020) summarized the significant lawsuits that assisted in the
realization and continual pursuance by state supreme courts and legislatures of adequacy in the
present day. These authors identify three critical waves of litigation. The first wave involves
plaintiffs challenging the funding disparities through the equal protection clause of the United
States Constitution. This wave began in the late 1960s and lasted into the early 1970s and is
marked by a small number of significant cases. Plaintiffs experienced minimal success using this
route. The critical court cases to consider here are McInnis v. Shapiro (IL), Burruss v. Wilkerson
(VA), Serrano v. Priest I (CA), and Rodriguez v. San Antonio (TX) (Odden & Picus, 2020). The
second wave of litigation referenced by Odden and Picus (2020) revolves around plaintiffs
challenging state equal protection and education clauses as opposed to the federal equal
protection clause. This wave picks up immediately following the first wave and carries into the
22

late 1970s. The significant cases here include Robinson v. Cahill (NJ) and Serrano v. Priest II
(CA) (Odden & Picus, 2020). When lawsuits began to be considered state by state through
education clauses, plaintiffs began to see more success. The third and final wave of litigation
mentioned by Odden and Picus (2020) emphasized plaintiffs challenging state education clauses
around the state’s failure to provide the level of education dictated by the state education clause.
This final wave of litigation was foreshadowed by the previous two waves but explicitly came to
light in the late 1980s and early 1990s. These court cases include the following: Rose v. Council
for Better Education (KN), Edgewood v. Kirby (TX), DeRolph v. State (OH), Montoy v. State
(KN), McCleary v. State (WA), Leandro v. State (NC), and CFE v. State (NY) (Odden & Picus,
2020). This third wave of litigation has shown plaintiffs more success than the preceding two.
The first wave of litigation sought to resolve the vast differences in per pupil funding that
existed between districts as a result of disparities in local property tax revenues. Plaintiffs
attempted to use the equal protection clause of the United States Constitution to show that in
certain geographic areas, students were not being given a suitable education in terms of resources
relative to more affluent, adjacent areas. If plaintiffs successfully litigated at the federal level, it
would mean a change for every state’s funding model. However, education is neither mentioned
nor assured by the United States Constitution, leading to nonexistent success for the plaintiffs.
Success for the plaintiffs means persuading the court to utilize the strict scrutiny test as
opposed to the rational basis test. The strict scrutiny test requires the state legislature to prove
that their model for funding schools exists in pursuit of a compelling interest, that it is not overly
broad, and that there is no less discriminatory means possible to achieve the goal of the law
(Odden & Picus, 2020). This is the preferred method of judiciality as it is very difficult for the
state to provide proof all three of these conditions exist in relation to the way the funding
23

structure of schools operates. The rational basis test is far more attractive for the state as it
simply has to prove a rational reason exists for the nature of school funding. This is as simple as
explaining schools are largely funded by local property tax revenues, which is a reflection of
local control, a common form of governance in the United States. Throughout the first and
second waves of litigation especially, these two tests played an extremely important role in the
results of lawsuits. For McInnis v. Shapiro (IL) and Burruss v. Wilkerson (VA), the state
prevailed as neither case granted the application of strict scrutiny, but rational basis.
Serrano v. Priest I (CA) garnered a great deal of media, policy, and legal attention
(Odden & Picus, 2020). In this proceeding, the plaintiff, under state of California constitution
and the 14
th
amendment of the United States constitution, was able to persuade the court to apply
the strict scrutiny test. This occurred, in part, as a result of the establishment of the standard of
fiscal neutrality, which essentially requires that educational expenditure not be a measure of local
property wealth (Coons et al., 1970; Wise, 1968). For the strict scrutiny test to be appropriate,
the law must be in violation of either a suspect classification or a fundamental right. In Serrano
v. Priest I (CA), the plaintiff was able to show that wealth per pupil was a suspect classification
and that education is a fundamental right, which had never previously been done in court. Coons
et al. (1970) argued that in addition to classifications like race and religion, local wealth per pupil
should not play a role in the quality of education provided by the public. This, along with Wise’s
(1968) work that called for education to be considered a fundamental right, cemented the
existence and consideration of fiscal neutrality in the funding of the public school system in
California. Unlike McInnis v. Shapiro (IL) and Burruss v. Wilkerson (VA), Serrano v. Priest I
(CA) successfully secured a strict scrutiny test over the use of rational basis at the state level,
paving the way for future court cases and ultimately foreshadowing the concept of adequacy.
24

While the court did not find the school finance structure in California unconstitutional, it
did rule that a system relying too heavily on local property taxes would indeed prove problematic
(Odden & Picus, 2020). Shortly after Serrano v. Priest I (CA), Rodriguez v. San Antonio (TX)
further enabled the application of strict scrutiny to the law and structure of public school finance.
Filed in federal court rather than a state court, the case eventually was appealed all the way to
the US Supreme Court which ruled five to four that education is not a fundamental right,
ultimately relying on the rational basis test. Not surprisingly, the court ruled that, in this case, the
Texas school finance structure was indeed constitutional. As the final significant case in the first
wave of litigation, Rodriguez v. San Antonio (TX) solidified the lack of success for plaintiffs
when using the equal protection clause of the United States Constitution. This result drove
plaintiffs to challenge state equal protection and education clauses, which ended up turning
future school finance litigation into an entirely state by state affair. The following Serrano case
was an example of this (Odden & Picus, 2020).
The second wave of litigation still showed more than half of the victories going to the
state. Plaintiffs, now challenging state equal protection and education clauses rather than the
federal equal protection clause, still did not have a great deal of success. The first critical lawsuit
of the second wave, Robinson v. Cahill (NJ), resulted in the court neither identifying property
wealth per pupil as a suspect classification nor education as a fundamental right under the state
equal protection clause. However, the significance in this lawsuit revolved around the ruling that
the state of New Jersey’s funding system was deemed unconstitutional under the state education
clause. This ruling gave birth, in some ways, to the concept of adequacy pursued today (Odden
& Picus, 2020).
25

The second and last, critical piece of legislation of the second wave, Serrano v. Priest II
(CA), truly moved litigation efforts forward for the plaintiffs. In California, not only did the court
apply the strict scrutiny test, acknowledging that education was a fundamental right and property
wealth per pupil a suspect classification, the court ruled the entire state funding system was
unconstitutional, and that the legislature was required to redesign the system to equitably fund all
public school students in the state. The state’s response was supposed to go into effect on July 1,
1978 and relied on a large state surplus to fund the system. The surplus was so large that, just
prior to the state’s enactment of the response voters passed Proposition 13 which forced major
changes and the development of a longer term solution for the next year. In essence, this decision
created awareness around funding systems and preempted states to begin looking more closely at
funding disparities within and across their school districts (Odden & Picus, 2020).
The final wave of litigation included a clear evolution by state supreme courts from
simply acknowledging the lack of fiscal neutrality in financial structures to incorporating much
more specificity in their rulings and decisions. Furthermore, state supreme courts were ruling
entire state funding systems unconstitutional under the respective state education clause. Many
of these lawsuits were defined by the court’s decision to begin tying funds to performance
assessments, such as in Rose v. Council for Better Education (KN). Additionally, rulings began
including a directive to divert more funds to students who demonstrated a higher need for
support, including low income and special needs student groups. In certain examples, such as
DeRolph v. State (OH), Montoy v. State (KN), and CFE v. State (NY), one can see how difficult
this move can be for state legislatures to design and implement systems that are both equitable
and adequate. One essential difficulty for states is finding enough money without increasing
local property tax rates to seemingly unreasonable levels.
26

In some cases, such as in Edgewood v. Kirby (TX), the legislature installed a recapture
like process where more affluent districts had portions of their property wealth redistributed to
other, property poorer areas for the purpose of school funding only. The court accepted this
solution – which was the third attempt by the legislature to meet the court’s standard. However,
the state also had to increase local required property tax rates to equalize per pupil funding.
Leandro v. State’s (NC) court ruling involved a directive to the state to provide preschool
for all low income three and four-year-olds. This act by the court illustrates a clear evolution
from McInnis v. Shapiro (IL) and Burruss v. Wilkerson (VA), who litigated based purely on the
idea of fiscal neutrality, and eventually equity purposes. Furthermore, in McCleary v. State (WA),
the court ruled the Washington state funding system unconstitutional and established that
increases in funding should be tied to some performance assessment, as opposed to simply
changing the way the funding formula operates. A change to the funding formula to more
appropriately distribute funds attempts to reach an equity framework, however, providing
preschool illustrates more of an adequacy framework; it attempts to not only get more funds to
the students who need it, but attaches a program to the funds.
The final case in the third wave of school finance litigation which plays a significant role
is the Abbott v. Burke (NJ) lawsuit. This series of proceedings began as a fiscal neutrality
argument with a focus on increasing the amount of funding going to students in 30 property poor
and disadvantaged school districts. It then developed into our modern form of adequacy litigation
when the court began providing a directive to the state to include funding based on content and
performance standards. Once standards were defined, the state began attempts to calculate the
cost associated with every student achieving the standard set. Lastly, like in Leandro v. State
(NC), the court required the state to provide preschool services (Odden & Picus, 2020).
27

The review of the litigation presented serves two purposes. First, it traces the birth of the
concept of adequacy through various court rulings. As Cubberley (1905) explained in the very
early 20th century, disparities in school funding as a result of unequal property value creates a
disparate system within and across the country’s public schools. Moreover, this review assists in
the explanation for the increase in the level of state funding from 16.5 percent in 1919-20 to 46.6
percent in 2014-15 (Odden & Picus, 2020). Second, the review serves to show how significant
the level of change can be when the courts become involved. Without the litigation efforts of the
past, the concept of and resources dedicated to achieving adequacy might be less developed and
affecting of change.
Taxpayer Equity
The largest source of income for public school districts has historically been local
property tax revenues. As Cubberly (1905) observed in the early 1900s, it has become
increasingly clear that for an equitable and adequate public education system to exist for most
students in the United States, this system of funding schools would have to be challenged or
altered. McGuire et al. (2015) summed up the problematic nature of using local property tax
revenues as the chief source of resources for an equitable, adequate public school system. These
authors cite the essential problem with using a majority local property tax revenue funding
structure is that local property wealth differs from district to district, which results in highly
variable tax rates to generate equal revenue, thereby creating perpetual, unequal revenues per
pupil. At the classroom level this ends up resulting in highly unequal PPE from one public
school district to another (McGuire et al., 2015).
School finance researchers generally point to three related concepts when efforts are
made to design policy and reform to the existing system of public school finance, specifically as
28

it relates to the way local property values are used: vertical equity, horizontal equity, and equal
opportunity (Rubenstein, 2016). These terms serve to give substance to the relationship between
money and the way it impacts choice and opportunity for students. The first term, horizontal
equity, attempts to evaluate whether or not students in similar situations with similar
characteristics receive similar resources (Rubenstein, 2016). This concept, while useful, appears
the least in reality as very few students face very similar circumstances and have similar needs.
This concept tends to focus on the idea of equality (Rubenstein, 2016). Vertical equity, while
much more apparent in the reality of public schools, attracts a great deal of support
philosophically, but in reality, policy and structure has often fallen short of providing this for
students. Equity and adequacy ideals tend to favor vertical equity as it furthers the notion that
students with different needs should receive different levels of resources (Rubenstein, 2016). The
final term, equal opportunity, focuses on whether or not resources correlate with factors such as
income and race, which fiscal neutrality (Coons et al., 1970; Wise, 1968) argued should be
present in our public education system (Rubenstein, 2016). Equal opportunity remains a
foundational concept in the efforts to move public education resource allocation to a more
equitable and adequate level, however, because local property taxes comprise a very large
percentage of funding for schools, most property rich areas continue to bring more revenue to
their students, while property poor areas continue to experience inequitable resource allocation.
Does Money even Matter?
The second, critical development in school finance that followed the issue of taxpayer
equity centered on determining whether or not money mattered in the context of schooling and,
more specifically, systematically improving student achievement using financial resources. One
of the seminal pieces written by Hanushek (1986) claimed there was no systematic relationship
29

between resources and student achievement. This large meta-analysis combined existing studies
at the time that attempted to find relationships between resources and achievement and
investigated the degree to which the results showed a statistically significant increase in student
achievement based on an increase in a financial resource. Hanushek (1986) also mentioned the
high degree of variability in schools with regards to the effective and ineffective use of
resources. He explains that in many cases schools resource their students and teachers effectively
which can lead to improved outcomes, however, he counters by mentioning that just as many
schools ineffectively resource their students. In terms of policy implications, one of his essential
points is that the design of policy around resourcing schools is highly complex. From an
economic perspective, ultimately, Hanushek (1986) asserted that a general increase in resources
would not broadly or generally increase student achievement.
In a direct counter, Greenwald et al. (1996) showed the opposite of Hanushek’s (1986)
work. These authors conclude, also using a meta-analysis technique, that school resources are
systematically related to achievement. Greenwald et al. (1996) criticized Hanushek’s (1986)
methodological approach of vote counting, explaining it to be a “rather insensitive” (p. 362)
technique for summarizing results of relevant studies. These authors claimed the approach is
rather outdated and rarely used in empirical research. Despite Greenwald et al.’s (1996) work,
Hanushek’s (1986) conclusions garnered a great deal of policy attention, with many continuing
to advocate for the worldview that a general increase in resources, particularly focused at PPE,
would increase student achievement on a general level.
Both Hanushek (1986) and Greenwald et al. (1996) focused on the inclusion of
production function studies in their analyses. Bowls (1970) defined educational production
functions as “the relationship between school and student inputs and a measure of school output”
30

(p. 12). Bowles (1970) explained that this type of methodology likely holds the most value for
determining the best way to allocate resources. However, as the literature shows, whether or not
money matters holds rich argument and polarization. Baker (2016) traced this question and cites
improvements in production function methodology that ultimately support the conclusion set
forth by Greenwald et al. (1996). Baker (2016) concluded by reaffirming the overwhelming
amount of improved scholarship supporting the notion that resources do matter and cited
Hanushek’s (1986) influential conclusion as “a source of doubt” (p. 19) that seems to further an
idea that schools may be able to do more with less, or that less resources may stimulate improved
outcomes.
Adequacy
The pursuit of resourcing an adequate education, by definition, is an attempt to determine
how much money is needed for PK-12 public schools to ensure that all students have the
opportunity to meet or exceed a state’s determined proficiency standards (Aportola et al., 2014).
This concept is significant as many states spend most of their budgets on their public education
systems. In sum, more than $300 billion dollars of revenues came from the state level for public
education in the United States during the 2016 fiscal year (NCES, 2018). This highlights the
importance of understanding how much money is needed to provide all students with the
appropriate education. As described above, with regard to state education clauses, the
significance of knowing how much a quality education costs is driven by more than just fiscal
influence but also constitutional influence. Furthermore, federal policies such as NCLB have
given public school districts accountability measures that include standards-based instruction.
The landscape of public education today includes a great deal more accountability and efficiency
31

expectations than it did when litigants and advocates were championing fiscal neutrality or
equity during the first wave of litigation.
Between 2003 and 2014, 39 adequacy studies were performed (Aportola et al., 2014).
Table 2 indicates where each of these studies took place. As evidenced in Table 2, many states
have engaged in inquiry around how much an adequate education costs for their public
school students. Oftentimes these adequacy studies occur as a result of a court hearing ruling the
state’s education funding system unconstitutional (Aportola et al., 2014). Another reason to
conduct an adequacy study, which falls under the same reasoning to conduct this study, is to see
how well a current funding structure provides the resources needed for an adequate education
(Aportola et al., 2014).

32

Table 2
Summary of State Adequacy Studies, 2003-2014
State Number of Studies
Maryland 2
Arizona 1
Arkansas 2
California 2
Colorado 4
Connecticut 1
District of Columbia 1
Illinois 1
Kentucky 3
Maine 1
Minnesota 2
Montana 2
Nevada 1
New Jersey 2
New Mexico 1
New York 2
North Dakota 2
Ohio 1
Pennsylvania 1
Rhode Island 1
South Dakota 1
Tennessee 1
Texas 1
33

Washington 2
Wisconsin 1
Wyoming 2
Total Studies 39

Note. Reprinted from Aportola, A., Picus, L., Odden, A. & Fermanich, M. (2014). A
Comprehensive Review of State Adequacy Studies Since 2003. Denver, CO: Augenblick, Palaich
& Associates. Copyright 2014 by Aportola et al.

There are four recognized methods for conducting adequacy studies. The Successful
Schools/District (SSD) approach relies on the concept that a particular district’s resource
allocation structures can be replicated from one district context that is meeting certain
achievements to another district context that may not be currently meeting a set of proficiency
standards. The Cost Function (CF) or Statistical Approach is the most complex and econometric
of the four. This method relies on significant amounts of data and on controlling various student
and school variables. Both the SSD and CF method estimate the cost of an adequate education,
but do not explicitly lay out where or how to allocate resources (Aportola et al., 2014). The
Professional Judgment (PJ) method depends on the expertise and knowledge of practicing
professionals to determine what resources are needed for a particular school or district. Lastly,
the EB approach applies existing education research on effective strategies and programs. This
method is the one that will be used in this study and it attempts to not only estimate the amount
of resources needed, but also how to strategically implement them to more reliably and
systematically achieve student access (Aportola et al., 2014). Together, these four methods help
schools, districts, and state legislatures determine how much it costs to provide students with the
34

public education that will give them all the opportunity to meet their state’s respective
performance standard.
Successful Schools/District (SSD)
The SSD method relies on identifying districts of similar context with regards to student
and societal demographics who are currently achieving at the desired level of the district seeking
to improve their student performance. Aportola et al. (2014) also noted that it assumes additional
funding will be needed in the district seeking to understand what it costs to provide an adequate
education. While rare, there have been cases where a state legislature or district has been found
to be spending more than what an adequacy study suggests. The central idea behind this method
involves replicating what a successful school district currently does in terms of resource
allocation, most specifically PPE and, if appropriate, weighted student funding formulas.
Aportola et al. (2014), in their summary of state adequacy studies between 2003-2014, showed
the SSD method to be used 18 times, primarily by the APA consultant group.
Cost Function (CF)/Statistical Approach
The cost function, or statistical approach, to determining school finance adequacy
contains a different methodological approach than the other three in some ways. First, this
approach can appear superficially attractive to clients and policymakers as it contains an aura of
objectivity (Costrell et al., 2008). Researchers who employ this method attempt to statistically
determine the cost needed to educate students to a given standard (Costrell et al., 2008). Another
element of this methodological approach is its overwhelming technicality and complexity.
Historically, when cost functions have been used in court settings, they are difficult to
understand and make decisions with. Researchers who have argued for the use of this
methodology claim that in the private sector, the concept of competition generally drives out
35

inefficient producers (Costrell et al., 2008). Researchers contend this idea can be replicated in the
field of public education.
The most critical limitation of this approach is in the extensive data needed at the school
level (Silverstein et al., 2007). The statistical equations needed to execute the CF method require
highly specific and unique data sets from a variety of areas, particularly if a study is being done
for a large school district or even a state legislature. Other authors have also commented more
generally on the difficulty in tying data to student achievement at the school level (Condron &
Roscigno, 2003). Condron and Roscigno (2003) explained that such data would greatly provide
insight into analyzing the link between school level expenditure and student achievement. The
other methods of estimating adequacy are viewed as less objective, but do not have similar
claims of causal or scientific relationship between the variables of resources and systematic
improvement in student achievement.
Once challenge posed by both the SSD and CF approaches is that while they estimate an
adequate level of funding for schools, they do not offer any suggestions for how those resources
should be allocated to improve student performance. Two additional methods, Professional
Judgment, and Evidence-Based, attempt to resolve this challenge by defining what a high
performing school looks like and then estimating the funding necessary to implement that vision.
Both are described below.
Professional Judgment (PJ)
In an adequacy study done in Montana, one of the primary consultant groups, APA
Consulting, describes the PJ method used. It is important to note, while the Montana PJ adequacy
study done by APA is being referenced here, many of the adequacy studies done in each
respective method follow similar procedures. The PJ method relies on panels, or groups of
36

experienced and knowledgeable practitioners in the field of education (Silverstein et al., 2007).
These panelists examine state and federal performance and accountability standards and share
the amount of resources they believe are needed to meet those standards or requirements
(Silverstein et al., 2007).
The result of the Montana PJ study is summarized in Table 3 below. Note that the base
cost is the PPE while the weights are additional funds for those targeted student groups. These
additional weights are noted in the parentheses for each classification. This is often referred to as
a weighted per pupil funding formula (Silverstein et al., 2007).
The weights for each of these dollar amounts have been added from a different table in
the Montana study. The PJ method operates under the assumption that the group of panelists has
the ability to identify the personnel, equipment, and programs needed to, in this case, have all
Montana students meet the state performance standards by the 2013-2014 school year, in
accordance with NCLB (Silverstein et al., 2007). Once the panel establishes these variables,
mathematical calculations are completed to arrive at a base cost, which is reflected in Table 3. In
this particular adequacy study, weighted costs were added for special need students.
The PJ method does not only include the use of a single panel of diversified experts. As is
the case with the Montana adequacy study done by APA, multiple panels are assembled to arrive
at the result seen in Table 3. For this example, school level, special needs, district, and statewide
overview panels were used, all building on each other, to appropriately determine the amount of
resources needed for Montana students (Silverstein et al., 2007). Each of these panels had a very
specific set of procedures, including looking at the following items: 1) personnel, 2) supplies and
materials, 3) non-traditional programs and services, 4) technology, 5) other personnel costs, and
6) other costs (Silverstein et al., 2007). Ultimately, the results of the PJ panel are communicated
37

in three primary domains: resource needs, prices, and base costs, including a per pupil weight in
this case (Silverstein et al., 2007).

38

Table 3
Summary of Montana PJ Panel Recommendations for PPE
School System Level Costs Including Adjustments for Size and Special Need Students (Based
on PJ Panel Work)
Hypothetical
District Size
Small Moderate Large Very Large
Enrollment 208 748 1,740 8,450
Total Base Cost $11,682 $9,459 $9,028 $9,030
Added Cost of Special Need Students
Mild $8,924(.76) $8,648(.91) $6,260(.69) $6,365(.70)
Moderate $14,646(1.25) $12,592(1.33) $13,341(1.48) $11,025(1.22)
Severe $31,420(2.69) $29,768(3.15) $30,700(3.40) $22,309(2.47)
At-Risk Students $2,866(.25) $3,720(.39) $3,316(.37) $4,537(.50)
LEP Students $9,310(.80) $7,181(.76) $5,418(.60) $4,472(.50)

Note: Adapted from Silverstein et al. (2007). Estimating the cost of an adequate education in
Montana. Copyright 2007 by Silverstein et al.

Evidence-Based (EB)
The EB model of school finance adequacy has been performed more than any other
method (Aportola et al., 2014). One of the strengths laid out by Aportola et al. (2014) is that the
EB model, unlike the others, involves the most up to date educational research regarding the way
resources, more specifically programs and services, should be used at the school level. While the
incorporation of research is a strength of this model, it is also a weakness, as sometimes there
may be a lack of research around certain cost elements schools face, whether the research can be
39

generalized to a specific student demographic or social context, and whether the research is
appropriate for a certain state (Aportola et al., 2014).
Odden and Picus (2016), in their EB adequacy study for the state of Maryland, explain
the importance for the use of what the authors term a prototypical school district and school.
These prototypical school and district sizes are used to aggregate costs and build out the
simulation using a variety of other inputs. In the case of Maryland, and in other cases, the EB
model has incorporated the use of PJ panels to assist in determining prototypical school sizes
(Odden & Picus, 2016). Once sizes and enrollments are determined, the EB model uses those
elements and attaches an evidence-based formula or dollar per pupil figure to calculate adequacy.
Table 4 displays the model elements along with the 2016 EB recommendations (Odden & Picus,
2020). Each of these specific elements are used, along with the prototypical school sizes, to
calculate the cost, per pupil, of an adequate education. As stated in the title itself, these are
evidence-based recommendations. These formulas comprise one essential piece of the overall EB
model for determining adequacy in resources. The other related piece comes from the school
improvement model. An updated version of the following model appears in Odden and Picus
(2020), which contains some changes, but highlights many of the same key principles.

40

Table 4
2016 Evidence-Based Model Elements and Formula Recommendations
Model Element 2016 Evidence-Based Recommendation
Staffing for Core Programs
1. Preschool Full-day preschool for children aged 3 and 4. One teacher
and one aide in classes of 15.
2. Full-day kindergarten Full-day kindergarten program. Each K student counts as 1.0
pupil in the funding system.
3. Elementary core
teachers/class size
Grades K-3: 15 (average class size of 17.3)
Grades 4-5/6: 25
4. Secondary core
teachers/class size
Grades 6-12: 25
Average class size of 25
5. Elective/specialist
teachers
Elementary schools: 20% of core elementary teachers
Middle schools: 20% of core middle school teachers
High schools: 33.33% of core high school teachers
6. Instructional
facilitators/coaches
1.0 Instructional coach position for every 200 students
7. Core tutors/Tier 2
intervention
One tutor position in each prototypical school.
(Additional tutors are enabled through poverty and ELL
pupil counts in Elements 22 and 25.)
8. Substitute teachers 5% of core and elective teachers, instructional coaches, tutors
(and teacher positions in additional tutoring, extended-day,
summer school, ELL, and special education)
9. Core pupil support staff,
core guidance
counselors, and nurses
1 guidance counselor for every 450 grade K-5 students
1 guidance counselor for every 250 grade 6-12 students
1 nurse for every 750 K-12 students, which supports a half-
time nurse in each prototypical elementary and middle school
and a full-time nurse in each prototypical high school.
(Additional student support resources are provided on the
basis of poverty and ELL students in Element 23.)
10. Supervisory and
instructional aides
2 for each prototypical 450-student elementary and middle
school
11. Library media specialist 1.0 library media specialist for each prototypical school
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12. Principals and assistant
principals
1.0 principal for the 450-student prototypical elementary
school
1.0 principal for the 450-student prototypical middle school
1.0 principal and 1.0 assistant principal for the 600-student
prototypical high school
13. School site secretarial
and clerical staff
2.0 secretary positions for the 450-student prototypical
elementary school
2.0 secretary positions for the 450-student prototypical
middle school
3.0 secretary positions for the 600-student prototypical high
school
Dollar per Student Resources
14. Gifted and talented
students
$40 per pupil
15. Intensive professional
development
10 days of student-free time for training built into teacher
contract year, by adding five days to the average teacher
salary
$125 per pupil for trainers
(In addition, PD resources include instructional coaches
[Element 5] and time for collaborative work [Element 4].)
16. Instructional materials $200 per pupil for instructional and library materials
$50 per pupil for each extra help program of poverty, ELL,
summer, and extended-day
17. Short cycle/interim
assessments
$25 per pupil for short cycle. Interim and formative
assessments
18. Technology and
equipment
$250 per pupil for school computer and technology
equipment
19. CTE
equipment/materials
$10,000 per CTE teacher for specialized equipment
20. Extra duty funds/student
activities
$300 per student for co-curricular activities including sports
and clubs for grades K-12
$50 per preschool student
Resources for Struggling Students
21. Tutors 1.0 tutor position for every 100 ELL students and one tutor
position for every 100 non-ELL poverty students.
22. Additional pupil support 1.0 pupil support position for every 125 ELL students and
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staff one tutor position for every 125 non-ELL poverty students.
23. Extended-day 1.0 teacher position for every 120 ELL and for every 120
non-ELL poverty students
24. Summer school 1.0 teacher position for every 120 ELL and for every 120
non-ELL poverty students
25. ESL staff for English-
language learner (ELL)
students
As described above:
1.0 tutor position for every 100 ELL students
1.0 pupil support position for every 125 ELL students
1.0 extended-day position for every 120 ELL students
1.0 summer teacher position for every 120 ELL students
In addition, 1.0 ESL teacher positions for every 100 ELL
students.
26. Alternative schools One assistant principal position and one teacher position for
every 7 ALE students in an ALE program.
27. Special education 8.1 teacher positions per 1,000 students, which includes:
7.1 teacher positions per 1,000 students for services for
students with mild and moderate disabilities and the related
services of speech/hearing pathologies and/or OT PT
This allocation equals approximately 1 position for every 141
students
Plus
1.0 psychologists per 1,000 students to oversee IEP
development and ongoing review
In addition
Full state funding for students with severe disabilities, and
state-placed students, minus the cost of the basic education
program and Federal Title VIb, with a cap on the number
covered at 2% of all students.
Staff Compensation Resources
28. Staff compensation For salaries, average of previous year
For benefits:
Retirement or pension costs: A state set %, per employee
Health insurance: ~$12,000-15,000 per employee
Social Security and Medicare: 7.65%
Workers’ compensation: .6%
Unemployment insurance: 0% as the state fully reimburses
costs
43

Note. Reprinted from Odden, A., & Picus, L. O. (2020). School finance: A policy perspective.
McGraw-Hill Humanities, Social Sciences & World Languages. Copyright 2020 by Odden and
Picus.

The 10 Strategies in the Evidence-Based School Improvement Model
The EB model has developed a school improvement strategy, which is embedded in the
EB funding model and based on the following 10 activities: 1) analyze student data, 2) set higher
goals, 3) review evidence on good instruction and effective curricula, 4) invest in teacher
training, 5) provide extra help for students at risk of academic failure, 6) restructure school days
to more effectively deliver instruction, 7) provide strong instructional leadership, 8) create
professional school cultures, 9) bring external professional knowledge into the school, and 10)
recruit and retain effective educators (Odden & Picus, 2016). Odden & Picus (2016) stated that
in many of their studies, educators share this view on how to improve schools, and also shared a
belief that if funds were used to effectively implement these strategies, significant gains in
student achievement would follow.
Odden and Picus (2016) stated that student data is the gasoline that drives effective
teamwork around improved instructional practice and, subsequently, student learning. Marsh and
Farrell (2015), in their theory of action for data-use, explained that data alone is not helpful, but
the collection, organization, and analysis of data can make it actionable. Given the increased
accountability tied to resources, as well as state and federal establishment of performance
standards, analyzing student data in relation to their students' proximity to achieving those
standards becomes critical to improvement. The EB funding model allocates one instructional
facilitator for every 200 students, making a clear incorporation of this research into their
44

recommendations. More coaches can facilitate greater reflectiveness and effective data analysis
among teachers. Additionally, the EB funding model provides 10 student-free days, which can
also be used for student data analysis.
Goal setting also plays a critical role in Odden and Picus’ (2016) school improvement
strategy. A rich research base supports the establishment of setting difficult goals and having
higher expectations for students. Locke and Latham (2006) discussed learning goals and state
that difficult learning goals lead to higher self-satisfaction and higher performance ratings such
as GPA. In terms of school finance adequacy and goal setting, specific numerical figures should
be tied to goals. Odden and Picus (2016) mentioned areas like Advanced Placement (AP) exam
participation, and having larger numbers of students perform better on standardized tests. Setting
more difficult goals can lead to greater improvements, even if the goals are not achieved. The
concept of goal setting is rooted in learning and motivation theory and has shown, historically, to
have great impact on performance inside of education (Zimmerman et al., 1992).
Odden and Picus (2016) highlighted the importance of teachers understanding and being
able to effectively utilize newly adopted curricula to see measurable improvements in student
achievement. The term high quality has come to be applied overabundantly in the field of public
education, particularly with the rollout of NCLB, where schools were required to hire only high
quality teachers as demonstrated by a certain level of training. Good, or high quality, instruction
must always be at the forefront of interactions between classroom teachers and students. Joyce et
al. (2009) explained that students who receive higher quality instruction demonstrate more
increased school learning than students who do not. Odden and Picus (2016) and their EB model
reflect the necessary resource formula in their model through elements like lower class size, and
the high ratio of instructional coaches to students, and therefore teachers.
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Darling-Hammond (2000) showed that investing in teacher knowledge, even over other
areas such as lowering class size, increasing salaries or even teacher experience, can have the
greatest implications for increasing student achievement. More specifically, Darling-Hammond
(2000) explained that knowledge around teaching, specifically a respective teacher’s content
area, can create the largest gains in student achievement. This aspect of Odden and Picus’ (2016)
school improvement strategy heavily synergizes with other elements in the strategy, including
establishing a professional culture, recruiting and retaining effective teachers, and increasing
instructional leadership capacity across a school site.
More recently, the strategy of providing extra help for students at risk of academic failure
has become formally recognized as building multi-tiered systems of support (MTSS) in schools.
This is the idea that some students may need additional support, outside of the classroom, to keep
up with academic skills and concepts taught. While originally considered to be an intervention
for special education populations, designing and implementing MTSS truly supports all students
with at risk backgrounds (Benner et al., 2013). Benner et al. (2013) explained that these
populations of students generally are the most prone to experience academic failure. Much of
this concept of providing extra help for students who need it rests in much of the school finance
context described in this literature review around equity, adequacy, fiscal neutrality, and
disparities in PPE.
Schools that are in lower property wealth areas generally contain higher populations of at
risk student groups. Historically, these schools also receive less funding than more affluent
counterparts. Given Baker’s (2016) argument that an increase in resources systematically
improves student achievement, these at risk student groups would achieve more with more
resources. To provide extra academic support for these student groups, greater amounts of
46

resources are needed. This is also where structures like weighted per pupil funding formulas can
greatly assist with realizing this principle. Within the EB funding model, extra resources in terms
of tutors and essential personnel are provided to struggling, or at risk, students (Odden & Picus,
2016).
Odden and Picus (2020) explained that the last several decades have seen increases in
schools offering elective courses, as well as increasing school days by adding additional periods
of instruction. Elective course offerings take up a finite amount of space in a school’s master
instructional schedule. This proliferation of elective courses, as these authors state, leads to these
classes having smaller sizes, thereby increasing budget constraints and creating a less effective
daily structure of instructional delivery. Odden and Picus (2020) ultimately argued that schools
who move the achievement needle in meaningful ways have a substantive liberal arts program,
but keep their resources focused on the core classes, such as math and language arts. The EB
model reflects serious investment of resources into liberal arts programs, but elements in the
model such as lower core class sizes reflect the most amount of investment, as reducing class
size has proven to be a very financially taxing change for school districts (Odden & Picus, 2011).
In this way, the authors suggest the school day be structured to reflect the most significant
investment into core classes, with less emphasis on the strength of elective programs.
Odden and Picus’ (2020) revised school improvement strategy framework includes
providing strong instructional leadership changes particularly to teachers and other staff at the
school site. This transition highlights the importance of developing teacher leaders who share the
ownership of the work being done collectively by the faculty of a school. This portion of the
school improvement strategy fits directly in with other elements such as having a professional
school culture and retaining effective educators. As stated above, higher quality instruction leads
47

to more student learning. The more distributed leadership is at a school site around instruction,
the more effective learning can be.
The work of DuFour (2004) accurately summarized the essence of what Odden and Picus
(2016) mean by creating professional school culture. DuFour (2004) addressed three major
points around creating professional school cultures. The first is a focus on ensuring that students
learn. This paradigm shift for most has to do with moving from ensuring that all students are
taught, to ensuring and making the mission of the school that all students learn. The second
major point is establishing a culture of collaboration. The power of collective teacher capacity is
reflected in Hattie’s (2012) meta-analysis, where collective teacher efficacy was shown to have a
much higher impact on student achievement than dozens of other instruction-related variables.
The final point DuFour (2004) emphasized is focusing on results. As discussed in DuFour and
DuFour (2013), the center of a professional school culture should be a focus on using results to
design goals. This cyclical process of focusing on results to move forward strategically is at the
heart of the professional learning community (PLC), and therefore, the professional school
culture.
Odden and Picus (2016) also emphasized the importance of seeking outside knowledge,
particularly high quality outside knowledge. This most specifically relates to the adoption of
curricula. In Odden and Picus’ (2020) revised school improvement strategy framework, the
authors stated that in nearly all cases of dramatically improving schools, instructional programs
and curricula are changed. The change from one instructional program to another must occur
through a highly informative, but effective process. The term expert is used in Odden and Picus
(2016) to reflect the type of knowledge schools should seek out when seeking to dramatically
improve student achievement.
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Recruiting and training effective educators is not only limited to classroom teachers, but
also the school leadership and administration, particularly the principal. Odden (2011) discussed
dramatic improvements in public school performance across urban districts in Boston, Chicago,
and New York, by focusing on managing human capital. These areas implemented highly
explicit and concentrated policies on improving the quality of their teachers and principals. In
terms of retainment, Burns and Darling-Hammond (2014), in their international teaching survey
covering over 30 jurisdictions in several different countries cited teacher self-efficacy as highly
related to lower burnout, and therefore, higher retainability. The idea of retainability and
recruitment has never been more important than it is now, particularly considering the work of
Ingersoll et al. (2014) around the “greening” of the teacher workforce (p. 11).
California’s Common Core State Standards (CCSS)
Up to this point the review of literature has encompassed a larger context. While state
standardized performance measures have been introduced and briefly discussed, the specific set
of standards used by California, termed the California Common Core State Standards, are
California’s version of this accountability system. These standards drive accountability for the
state and assist the state in determining the extent to which certain districts, schools, and students
require more resources or access to more programs. The CCSS are a manifestation of not only
the shift in increased funding coming from the state, but the accountability measures that go
along with provision of state resources.
In the seminal CCSS document, Jerald (2008) explained the rationale and justification for
the implementation and rollout of the standards. Because this study takes place in California, a
brief explanation for the origin and development of CCSS is critical. The rise of the CCSS comes
from an effort by policymakers and governments to compare and compete by “benchmarking”
49

the outcomes of one group with another to determine which is more effective (Jerald, 2008). The
CCSS is the result of these groups attempting to measure the quality of public education in the
United States internationally. Furthermore, the CCSS embody the drive for governments to
produce innovative and competitive economies on the global stage. These groups recognize that
education is an important element in driving this innovation. An essential element of defining
and resourcing adequacy is highly dependent on the state performance standards. In California,
adequacy is determined by calculating a base cost for the level and use of resources needed for
all students in California to have an equal opportunity to meet the CCSS. Jerald (2008) cited five
actions in the document, which the National Governors Association (NGA) support.
The first action involves the formal adoption of internationally recognized standards in
math and language arts. The second action heavily echoes the importance of the concept of
adequacy as it essentially states that resources should be aligned with the standards. The third
action, also referenced in the EB educational research component, revolves around the
recruitment and retainment of high quality teachers and leaders. Action number four; or the
implementation of accountability systems, communicate the need to hold educational systems
accountable through a combination of interventions and support to reach internationally-
established best practices. The fifth action; the measurement of performance in a global context,
summarizes one of the chief concerns of the document, which is that the United States’ quality
and product of public education has fallen behind globally. This final action involves the
measurement and comparison of United States students with the global context, particularly as it
relates to productivity in the 21st century economy (Jerald, 2008).
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Gap Analysis Approach
Embedded within the use of all four of the identified school finance adequacy methods is
the concept of a gap analysis (Clark & Estes, 2008). It is critical to consider this concept in the
body of literature for this study, particularly because it seeks to establish and provide a solution
for a productivity or results gap in the organization of focus. While the Clark and Estes (2008)
gap analysis framework focused on knowledge, motivational, and organizational barriers that are
creating the effectiveness gap, within the context of school finance adequacy and resource
allocation, it remains appropriate to consider. It is likely that a certain level and use of resources
impacts the presence and influence of these types of barriers within an organization.
Within the EB model specifically, the outputs for the model include three facets. The first
is the current level and use of resources in the particular school, district, or state legislature. The
second is the desired level and use of resources by the client. The third is oftentimes what the EB
model of school finance adequacy suggests. The differences between these figures often serve to
expose a gap, in some way, between the current level and use of resources and what the EB
model provides. What the EB model provides, however, over the other methods, which is also
referenced in the Clark and Estes (2008), is an implementation strategy, particularly around the
use of goal setting and effective leadership.
Nontax Revenues
The literature on the use of school foundations, such as the San Marino Schools
Foundation (SMSF), is minimal. Some scholars discuss the term “nontax revenue” which are
local revenue sources that are not generated through something like a property or income tax
(Killeen & Downes, 2016). These authors speak most specifically about fee collection; however,
the idea of a school foundation would be situated under a nontax revenue. Furthermore, the link
51

to these nontax revenues to their impact on student achievement is less existent. What the
research does suggest, however, is that these nontax revenues comprise a very small portion of
funding for public education at just 3% of local sources in 2012-2013 (Killeen & Downes, 2016).
This sheds even more light on the uniqueness of the SMSF given it provides more funding than
3% of general fund revenues. One appropriate notion, however, associated with the foundation as
a nontax revenue is the question of equity. Something like a foundation must use its funds not for
a specific student or group of students, but to provide resources equitably at the school level.
Killeen and Downes (2016) suggested the question of equity may be problematic around the use
of nontax revenues in education.
Perhaps the most significant research done on nontax revenue by Downes and Killeen
(2014) suggested that in the greater context of school finance equity and adequacy, nontax
revenues have played a small part. Downs and Killeen (2014) based their work on the principle
that nontax revenues would be used by local entities to reduce the reliance on local property
revenues. The authors found that this effort has largely been ineffective. Nontax revenues have
not succeeded in any measurable way in taking away the reliance on local property value. This
literature is significant as the current context in focus for this study may represent an outlier for
this given principle. Even in times of greater fiscal pressure, such as the Great Recession, noted
by these authors, or even COVID-19 as a current example, locales do not turn toward nontax
revenue to offset revenues generated by local property wealth. This research should be revisited
given the outcomes of the current study that are discussed later.
Summary of the Literature
The development of adequacy, as a concept and tool for reducing disparities in funding
within and across states, has developed in large part from the history of litigation efforts.
52

Reforms to state legislatures to create and implement more equitable funding formulas have been
most heavily influenced by significant court rulings that find current systems unconstitutional
under state education clauses. These litigation efforts align with prevalent conversations among
researchers and scholars around concepts like taxpayer equity as well as the fundamental
argument around whether or not money matters in the context of quality for the public education
system.
The pursuit of adequacy for public education systems has largely become the work of
consultants and education finance experts. Four prevalent models have embodied the
operationalization of adequacy in education organizations. These four models; the Professional
Judgement, Cost Function, Successful Schools, and Evidence-Based, rely on different processes
and methods to produce results for organizations seeking to redirect or increase resources to
schools and students who need them. The EB model demands more attention as it is the model in
use for the given study. This model, unlike the others, incorporates a substantial empirical
research base of principles and programs that have been shown to have positive effects on
student achievement, regardless of context.
School finance adequacy is driven, in large part, by a state’s established educational
performance standards. Adequacy models assist in determining the amount and target of
resources needed for all students in a given organization to achieve at the appropriate
performance standard. The state in question for this study is California, which has developed and
uses the CCSS. These standards are significant for adequacy models as they are the metric of
success for students in California’s public education system. State performance standards are
also a result, in recent decades, of a move toward higher accountability and conditional ties to
resources that are given at the state level. With the described shift in resource dispersion from the
53

local level to the state level, more accountability structures have been developed. The CCSS are
one example.
The EB model, and all school finance adequacy approaches, attempts to define and
explain a gap, either in funding or efficacy of resource allocation. For this reason, the gap
analysis framework plays a significant role. While Clark and Estes (2008) provided the formal
gap analysis framework that describes gaps in knowledge, motivation, and organizational factors,
an adequacy study attempts to define gaps, but concentrates most efforts around financial
variables, such as PPE and staffing ratios. Moreover, some of the gaps that an adequacy study
might reveal are embedded in organizational factors, making it aligned, in some part, with the
formal gap analysis framework.
Lastly, the literature around nontax revenue plays a significant role in this study as the
district in question operates a school foundation, which brings in resources outside of the local
property tax revenue generation. While the literature around nontax revenue suggests it does not
have a significant impact on funding, for the SMUSD, it may indeed be significant. The context
in question may provide contradictory to the literature based on findings and conclusions drawn
later in the study. The body of literature referenced and described serves to provide a lens
through which to view the following study.

54

Chapter Three: Methodology
This study examines how the San Marino Unified School District (SMUSD) uses both
Local Control Funding Formula (LCFF) and other locally generated revenues to resource their
students’ education. Further, the examination was performed through the lens of school finance
adequacy, using the Evidence-Based (EB) model developed by Odden and Picus (2020).
Resources in the SMUSD were examined first in isolation, looking specifically at how each
individual revenue stream; the LCFF, parcel taxes, and San Marino Schools Foundation (SMSF),
manifests at the school level in terms of resources, particularly personnel. Then, all of the
district’s resources were compiled and compared to the suggested level of resourcing provided
by the EB model’s recommendation.
The EB model used SMUSD’s demographic data and accounting and financial records to
build its suggested level of resource allocation. The EB model includes both a quantitative
element in its formulas and personnel resourcing calculations, and also an element of educational
literature to support the ratios it uses. The model is based on the following ten principles: 1)
analyzing student data, 2) setting higher goals, 3) reviewing evidence on good instruction and
effective curricula, 4) investing in teacher training, 5) providing extra help for students at risk of
academic failure, 6) restructuring school days to more effectively deliver instruction, 7)
providing strong instructional leadership, 8) creating professional school cultures, 9) bringing
external professional knowledge into the school, and 10) recruiting and retaining effective
educators (Odden & Picus, 2020). The data for this study were collected from district documents
that outline variables related to resource allocation such as enrollment, subgroup populations,
class size, full time equivalent (FTE) positions, pupil-teacher ratios, and many others. All of the
55

data originate from the SMUSD itself. No financial data was taken from outside of the school
district as an organization.
This study followed a quantitative analysis framework. I was not seeking to establish
causation between an independent and dependent variable and did not employ the use of any
controlled experiments to study a particular variable. I gathered and analyzed quantitative data to
shape a narrative around the concept of school finance adequacy in the SMUSD. The data
collection for the study was done entirely by me. The chief goal of this quantitative analysis was
to illustrate, or tell a story, using quantitative data, of the degree to which SMUSD delivers an
adequate education using various revenue sources, examined first independently, then
collectively. I used the context developed in chapters one and two of this study to frame and
design the methodology. The data analysis section of this chapter outlines very briefly the
different pillars of the study.
Research Questions
RQ 1: What resource allocation gaps does the Evidence-Based model of school finance adequacy
estimate for the San Marino Unified School District (SMUSD)?
RQ 2: What are the implications of these findings for the allocation and use of both LCFF and
other locally generated resources in the San Marino Unified School District?
Sample and Population
I employed the use of purposeful sampling in this study. A purposeful sample is defined
as an information-rich sample that is most effective given a limited use of resources (Patton,
2002). The sample consisted of all four comprehensive schools located in the SMUSD. One
essential reason for selecting the SMUSD was the uniqueness of the district in terms of the
locally generated revenues it uses outside of the state’s LCFF. According to Ed-Data (2019), the
56

SMUSD possesses 651% more resources in other local revenue than the average unified school
district in the State of California. Additionally, given my access and time constraints, this sample
made the most effective use of time and resources given the parameters of the study. I
understood the subjectivity involved in this convenience sample, however, my aim and purpose
for the study was to inform the SMUSD about how it uses resources and to what degree the level
and use of resources provide an adequate education for its students based on the EB model.
I limited the population to the state of California as every state can have vastly different
funding formulas and structures for their public education systems. All comprehensive, public
schools in the state of California, however, are situated under the LCFF. As stated in the
literature review, disparities in funding are a product of most state’s funding structures, and
should not be an indication that the SMUSD is not a representative sample in the population of
public, comprehensive schools in the state of California. Disparities exist within and across
school districts, counties, and states (National Research Council, 1999).
Overview of the District
The SMUSD is a small public school district, containing approximately 3,000 students. It
is located in the San Gabriel Valley between East and South Pasadena. The district has been
consistently recognized as one of the highest performing public school districts in the state of
California according to standardized tests. The California School Dashboard (2017) shows
SMUSD’s English Language Arts performance to be 99.9 points above the standard while the
rest of California is only 2.5 points above the standard. Similarly, for mathematics, the district’s
scores are 91.7 points above the standard, while the remainder of the state is 33.5 points below
the standard. Other metrics of the school dashboard such as College/Career readiness also show
the SMUSD to be among the top performers in the state.
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Table 5 showcases some of the critical variables that were used in the EB model’s
resource allocation calculations. Much of the suggested resource allocation outputs in the EB
model came from inputting enrollment, percentages of English Learners, socioeconomically
disadvantaged, and special education populations.
Table 5
2018-2019 SMUSD Demographics
School
Name
Enrollment English
Learners %
Foster
Youth %
Socioeconomically
Disadvantaged %
Special Education
Percentage %
Carver
Elementary
599 17.9 0 7.3 8.2
Valentine
Elementary
553 14 0 4.3 5.4
Huntington
Middle
School
700 10.3 0 6.1 9.1
San Marino
High
School
1,101 8.4 0 9.8 6.7

Note. Adapted from the California School Dashboard. (2017). San Marino Unified School
District information [Infographic]. CASchoolDashboard.org.
https://www.caschooldashboard.org/reports/19642460108407/2019/schools. Copyright 2017 by
the California School Dashboard.

58

Instrumentation and Data Collection
The primary data collection instrument for this study was dictated by the inputs needed
by the EB funding model. This is an Excel model that allows for the input of many different
variables to produce the EB funding recommendation in comparison with the current levels of
funding and resource allocation. There is also space in the EB Excel model to input the district’s
desired level of resources. This Excel model played the foundational role for the development of
the narrative as it relates to the study’s overall purpose of determining the extent to which the
SMUSD is resourcing its students for an adequate education, as recommended by the EB model.
This Excel model ultimately produced two scenarios which I used to interpret findings and
perform analysis: 1) the current circumstances surrounding resource allocation in the SMUSD as
well as 2) the recommended resource allocation structure for the district based on the EB
model’s educational research suggestions. These results were then compared with the current
allocation of resources used by the SMSF, in addition to other locally generated revenues used
such as the parcel taxes.
The collection of data began in the summer of 2020 and was comprised of the most
current data from the 2020-2021 school year. Where data from prior fiscal years was used, it is
noted in the limitations of the study and data descriptors such as table names and through
language in the body of the paper. The study began as a collection of many different financial
reports obtained through the SMUSD office administrative personnel and public information
available from board meetings and the district website. I first began by looking through prior
board meeting presentations for useful data relevant to the study. Furthermore, the I accessed all
available accounting and business documents available to the public. The aim for data collection
was to gather all information related to resource allocation, per pupil funding, overall funding
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and expenditure documents as well as site level resource allocation documents such as master
schedules and the Single Plan for Student Achievement (SPSA) report done by each principal
and their respective School Site Council (SSC).
The most essential piece of data was provided by the director of accounting in the
SMUSD central office. This Excel file, titled the “20-21 Employee List,” contained critical
information regarding personnel and their funding source, certificated or classified status, as well
as their work locations. All personal information was redacted from the data. What was
ultimately left provided the largest source of inputs for the EB Excel model related to staffing.
Most resources in public school districts are spent in human resources, making this piece of data
foundational to the efficacy of the study as the findings below reflect heavy investigation and
analysis of these staffing and full time equivalent (FTE) human resources. Critical data in the
Excel file included FTE information, job title, and funding source. As seen below in the findings,
much of the outputs from the EB model relied heavily on this particular piece of data I collected.
In addition to individual collection of available data, informal meetings and
communication also took place between myself and the district CBO and director of accounting
between the period of August and December of 2020. These meetings occurred in an effort to
provide data that might have been left out of or difficult to find in the available public
documentation. I also needed assistance clarifying information presented in the financial
documents collected individually. No formal timeline of meetings or subjects of conversation
will be recorded. Given the fact that the SMUSD is a government entity, all financial reports and
occurrences were made available to me and are available to the greater public.
60

Data Analysis
The data analysis for the study took place over a period of six months from August 2020
to February 2020. Once all relevant data from the 2020-2021 school year was collected,
determined first and foremost by the requirements of the EB model, I began inputting data into
the EB model through Microsoft Excel. The manner of analysis took place as follows:
• An examination of current levels of resource allocation in the SMUSD using only the
Local Control Funding Formula grant
• A comparison between current levels of LCFF resource allocation and the Evidence-
Based model’s suggested level and amount of resources
• An examination of the use of resources from non-LCFF revenues, or the San Marino
Schools Foundation and parcel taxes
• A comparison of all of SMUSD’s revenue sources with the EB model’s suggested
amount and level of resources
The data analysis began as a series of tables and spreadsheets, with data visualization that
allowed me to piece together the narrative for how all of the different revenue sources in the
SMUSD help to bring an adequate education to its students. I isolated two specific findings from
the EB model: FTE positions and revenues. After isolating these two specific variables, I then
extrapolated the gap analysis outputs from the EB model and began examining the data with its
relationship to the EB model prescriptions (see Table 4).
Where gaps appeared indicating substantially less or more resources or FTE being
allocated in the SMUSD as a whole or at a specific school, I made note for discussion in chapter
four of the study. I focused most efforts on explaining and unpacking substantial gaps in the EB
model outputs to narrow focus on effective and substantial implications and policy
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recommendations for the district. Areas of the gap analysis for revenue and FTE that were not
significant, or that demonstrated an alignment in resources between the SMUSD and EB model,
may not be discussed in the following chapter, but appear in provided tables (see Tables 9, 11,
13, and 15).
Taking into account all of the data and the formulation of the narrative, a set of
recommendations and suggestions for bringing the SMUSD closer to adequacy given all of its
revenue sources is provided in chapter five of the study. Findings and further explanation are
provided in the remaining two chapters of the study with chapter four laying out the findings and
chapter five describing implications, policy recommendations, and limitations of certain areas of
the analysis. The findings in the following chapter begin with an overview of the study, followed
by an analysis and description of significant findings beginning with the entire district, followed
by the high school, then the middle school, and then the elementary level.
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Chapter Four: The Findings
Introduction of the Findings
Despite the San Marino Unified School District’s (SMUSD) affluent real estate market,
far above average test scores, low relative class sizes, and an abundance of local revenue
generation outside of the Local Control Funding Formula (LCFF), the Evidence-Based (EB)
model still shows a resource gap for the district’s students in the millions of dollars of revenue
and dozens of full time equivalent (FTE) certificated positions. Without the additional locally
generated revenues the district receives, the EB model’s recommendations create even more of a
dearth landscape for not only the way resources are allocated, but also the sheer number of
resources available.
These findings present a complex and politically conflicting image of the public school
finance structure for the SMUSD. As the literature clearly suggests, the financing of our nation’s
public school system has shifted, in large part, from a largely local endeavor to a state influenced
process. Furthermore, as the state has taken more control over the way school districts are
financed, there has been a great emphasis on balancing the per pupil expenditures (PPE) across
the geographic landscape regardless of local property values using things like weighted per pupil
funding formulas. For the SMUSD to maintain its longstanding tradition of excellence and
community expectations it must raise millions of dollars in local revenue generation, only to still
fall substantially short of the EB model’s recommendations.
Experts might suggest San Marino students may only need a relatively small share of
state resources to still perform incredibly well on state standardized tests given the fact that the
district enrolls relatively few poor or foster care students. Further, the view, in some areas, is that
the LCFF is working exactly as intended by providing a relatively small share of resources to the
63

SMUSD. As a district nestled in the center of a group of wealthy, prestigious private schools and
a highly demanding community, however, local employees and longstanding servants of the
SMUSD likely argue otherwise.
Overview of the San Marino Unified School District
The SMUSD budget includes three central streams of revenue; the LCFF, generated
largely through local property taxes as directed by state law and fully funded through state funds
as needed to reach the LCFF funding level, the San Marino Schools Foundation (SMSF)
donations which constitute nontax revenue, and two parcel taxes. It is the norm for most school
districts to generate almost all their revenue from the LCFF. SMUSD is in a unique position to
generate substantial revenue from both its foundation and from parcel taxes. During the 2019-
2020 school year, the LCFF base grant for SMUSD was approximately $25,000,000. The district
received virtually no supplemental or concentration grant monies from the LCFF due to the
extremely low unduplicated count of students from low income homes, English Language
Learners and foster children. The SMSF and parcel taxes generated nearly $8,000,000 in
additional funding during the same academic year. This means roughly 30% of the revenue
generated by the SMUSD does not come from the LCFF. The findings outline the current
allocation of resources in the SMUSD as well as the specifics around the way the district
allocates these other locally generated resources. One finding of the study explains how the
SMSF and parcel taxes seek to meet the standard of adequacy produced by the EB model.
Given the focus on financial resources and staffing levels in this study, some particular
figures are worth noting as the findings from the study the study are reported. Table 6 displays
expected PPE for the 2019-2020 school year, projected revenue assumptions from 2018-2019
through 2021-2022, and key expenditure assumptions from 2018-2019 through 2021-2022.
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Much of the data collection and analysis for the study revolves around these attributes of the
SMUSD. For the purposes of this study, I was interested in the current reality of the way
resources are spent in the SMUSD, as well as what the EB model recommends. Table 6 also
outlines the other locally generated revenues that support the district, which equate to millions of
dollars in resources. The most critical figure to consider in relation to the findings of the study is
the per pupil expenditure gap between the current level of resources in the SMUSD and what the
EB model suggests. As shown further in the findings, the EB model shows a substantial dollar
per pupil spending gap for the district and an overall revenue gap.

65

Table 6
2018-2022 SMUSD LCFF PPEs, Key Expenditures and Revenues Assumptions
2019-2020 Local Control Funding Per Pupil
Grade Level Base Grant Augmentation Grants Total Grant
TK-3 $7,702 $801 $8,503
4-6 $7,818 - $7,818
7-8 $8,050 - $8,050
9-12 $9,329 $243 $9,572
Key Expenditure Assumptions
2018-2019 2019-2020 2020-2021 2021-2022
Certificated
Salaries
$17,424,148 $17,820,606 $17,048,806 $16,689,606
Classified
Salaries
$8,377,833 $8,415,667 $8,455,667 $8,615,667
Employee
Benefits
$10,165,358 $10,695,813 $10,961,225 $11,017,040
Books and
Supplies
$2,529,906 $1,371,792 $1,288,328 $1,244,447
Operating
Expenditures
$5,406,039 $4,050,641 $3,950,641 $3,950,641
Equipment $843,918 $310,000 $210,000 $210,000
Total $44,747,202 $39,064,519 $41,914,667 $41,727,401
Key Revenue Assumptions
2018-2019 2019-2020 2020-2021 2021-2022
Student
Enrollment
2,967 2,935 2,904 2,853
LCFF Funded
ADA
2,992.37 2,906.68 2,860.10 2,830.03
Increase in
LCFF Funding
$1,500,042 $188,283 $359,436 $450,904
One-Time State
Funding
$549,516 - - -
Federal
Revenues
$1,020,571 $1,024,743 $1,024,743 $1,024,743
Schools
Foundation
$2,149,000 $2,000,000 $2,000,000 $2,000,000
Parcel Taxes $5,800,000 $5,924,500 $6,102,235 $6,153,220
Total $11,019,129 $9,137,526 $9,486,414 $9,628,867

Note. Adapted from Boucher, J. (2019, June 11). 2019-2020 proposed budget and long-range
financial projections. [PowerPoint slides].
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https://www.smusd.us/pdf/13_a_201920ProposedBudgetPresentation_0.pdf. Copyright 2019 by
Boucher, J. Future year projections include potential budget savings and reductions. Total
revenue amounts do not include LCFF Funded ADA base amount.

Breakdown of Revenue Sources by FTE for the SMUSD
To begin a review of the findings, it is important to provide an overall image of the
funding sources for the district by looking at certificated FTE. The essence of the study revolves
around understanding the extent to which the SMUSD provides its students with an adequate
education using all of its revenue sources. The highest leverage variable for looking at adequacy
revolves around certificated FTE resources, or staffing resources. As the review of literature
shows, the field of education has moved in a direction requiring a higher quality of labor with
more skills and training, dissimilar to other fields like manufacturing and technology. Further,
the study hones in on the implications that local revenue generation has for the SMUSD and
educational landscape that might exist without the aid of these other locally generated revenues
such as the schools foundation or the parcel taxes.
Table 7 identifies each school in the SMUSD and outlines how many FTE are provided
by each source of funding. Other locally generated revenues in Table 7 include everything aside
from the LCFF, Title I, and SPED. These three revenue sources are provided by either the state
or federal government. SPED and Title I are included in Table 7 for objective information,
however, the essence of the study encompasses the LCFF and the other locally generated
revenues. As a reminder, all of these local revenue generation sources are generally renewed,
allowing the district to depend, in some sense, on the revenue.
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This does not apply to the We Are San Marino funding; this funding was a one-time
allotment from the SMSF to offset reductions in force due to declining enrollment. At the
conclusion of the 2019-2020 school year, the district faced the need to perform a reduction in
force of 14 teachers. The SMSF agreed to fundraise the money to bring back these 14 teachers
for a single year. These funds, unlike the standing endowment from the SMSF to the district, or
the parcel taxes which are renewable, were designed to fill a gap in revenue for the 2020-2021
school year which largely occurred due to declining enrollment. For the remainder of the study,
the We Are San Marino funding will appear in the funding provided by the SMSF. It is separated
from the SMSF only in Tables 7 and 8 because its meaningful size and also to provide further
context and information. Lastly, the methodology of the study committed to using human
resources data from the 2020-2021 school year, which includes the one time We Are San Marino
grant of 14 FTE.
Table 7
2020-2021 SMUSD Certificated FTE by Revenue Source
Location

Funding Source
LCFF We Are
San
Marino
SMSF Parcel
Tax #1
Parcel
Tax #2
Title
I
SPED Total
Valentine 17.1 3 4 1 4 0 3.8 32.9
Carver 17.7 3 4 1 4 0 4.8 34.5
Huntington 8.7 2 5 3.8 9.6 0 6.9 36
San Marino High 16.7 6 7 5 15 1 5.9 56.6
Total 60.2 14 20 10.8 32.6 1 21.4 160

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Table 8 outlines the same data as provided in Table 7, except the figures are presented as
percentages. As evidenced by Table 8, local revenue generation becomes more and more applied
as students enter the middle school and then the high school, with only 29.5% of the revenue
coming from the state’s per pupil funding formula, whereas over 50% of the certificated FTE
allotments at the elementary schools come from the LCFF. The middle school employs the
smallest portion of the LCFF for certificate staffing, whereas Parcel Tax #2 provided the largest
percentage of certificated FTE. An important note to consider is that Parcel Tax #2 provides
more funding for the middle school than the state’s funding tool. This is also evident at the high
school if the revenues from both parcel taxes are combined. This finding alone demonstrates the
significant amount of financial investment on the part of the community to support the SMUSD
at the secondary level.
Table 8
2020-2021 SMUSD Certificated FTE by Revenue Source as Percentages
Location

Funding Source
LCFF We Are
San
Marino
SMSF Parcel
Tax #1
Parcel
Tax #2
Title I SPED Total
Valentine 51.9% 9.1% 12.1% 3% 12.1% 0% 11.5% 100%
Carver 51.3% 8.7% 11.6% 2.3% 11.6% 0% 14% 100%
Huntington 24.2% 5.6% 13.9% 10.6% 26.7% 0% 19.2% 100%
San Marino
High
29.5% 10.6% 12.4% 8.8% 26.5% 1.8% 10.4% 100%
Total 37.6% 8.8% 12.5% 6.8% 20.4% 0.6% 13.4% 100%

69

While it is evident that the district receives virtually no Title I revenue to fund
certificated staffing positions at the school sites, SPED takes up a meaningful amount of
certificated staffing, particularly at the middle school. SPED funding falls outside of the
significance of the study, especially considering that, on average, the federal government still
only contributes roughly 10% on average to public education across the country (Springer et al.,
2015; Gordon, 2015). Furthermore, as the findings outline later, the SMUSD over allocates
staffing in the area of SPED, according to the EB model outputs and the research it uses to build
its recommendations.
Evidence-Based Model Outputs for the SMUSD
The following section of the findings details the core outputs provided by the EB model
of school finance adequacy generated by inputting staffing or FTE allocations, student
demographics, and various dollar resources. For review, the EB model provides quantitative
figures founded on a deep empirical base of educational research, different than any of the other
methods of determining what level of resources are needed to achieve adequacy for a given
school district.
The greatest percentage of resources in any public school district goes toward positions
and people. The following section outlines potentially the most significant finding of the study as
it lays out the SMUSD’s resource allocation levels collectively. I begin by laying out findings for
the district and then sequentially covers the single high school, single middle school, and lastly
the two elementary schools in the district. These findings establish certain trends and patterns in
the district that are seen later in the specific school site findings. Only the most notable findings
are described in the following tables, and the tables themselves should be viewed by readers for
specific positions and results produced by the EB Excel model.
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It should also be noted that in various portions of the findings and tables in the following
sections, certificated FTE are occasionally presented, and at other times total FTE are presented.
Certificated FTE are isolated as they are considered the chief drivers of student achievement and
quality of instruction. Furthermore, in the review of the literature, much of the discussion around
resource allocation, trends in PPE and student ratios, have emphasized certificated positions. The
EB model does include and provides explanations around the significance of classified positions.
Table 9 displays both certificated and classified findings for the SMUSD as a whole.
Tables 9, 11, 13, and 15 represent a comparison of all the current SMUSD resources and
the level of resources generated by the EB model as well as the FTE gaps computed by the EB
model at each level within the district. More specifically, current SMUSD resources means a
combination of the total LCFF grant, both parcel taxes, and the SMSF. For these tables, I relied
on the EB Excel model to produce the outputs seen in the gap analysis. I used SMUSD human
resources and accounting data and input certain data points into the appropriate cells in the EB
model. The EB Excel model has formulas built in that are driven by ratios established by a
comprehensive base of educational research. These ratios are best demonstrated by viewing
Table 4. The Excel model takes the raw data from the SMUSD and exposes it to the Excel
formula within the EB model to create the results illustrated in the following tables. The first
column in these tables is a gap between the recommended revenue by the EB model and the
current revenue of the school district. The second column is a gap between the recommended
FTE by the EB model and the current FTE allocations of the school district.
Revenue Differences and Staffing for the SMUSD
Table 9 lays out the findings extracted from the EB model’s Excel output, specifically for
staff in the SMUSD as a whole. These findings combine the findings in Tables 11, 13, and 15 to
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produce the overall revenue and FTE gap in the district. This finding allows the research to
describe trends and notable occurrences at a broader level. As findings at both the primary and
secondary levels are laid out, it will be helpful to examine the way findings in the smaller context
reflect findings at the district level. Indeed, the high school, middle school, and elementary levels
in the SMUSD reveal some patterns that are representative of the cumulative district findings.
However, findings will also be discussed that reflect gaps, or overallocations, at certain levels of
education within the district.
Table 9
Evidence-Based Model Gap Analysis for Total SMUSD Revenue and FTE
Position All Current SMUSD Revenue FTE
Principals $0 0
Assistant Principals ($100,918) (.72)
Instructional Coaches ($1,368,122) (12.06)
Core Teachers ($3,731,551) (32.88)
Specialist Teachers ($776,998) (6.85)
SPED Teachers $120,734 1.06
ESL Teachers ($22,698) (.20)
Academic Extra Help Staff ($864,542) (7.62)
Non-Academic Pupil Support ($297,949) (2.63)
Nurses ($425,361) (3.75)
Extended Day/Summer
School Staff
($179,693) (1.58)
Instructional Aides $766,015 13.53
Supervisory Aides ($562,933) (7.48)
SPED Aides $1,989,923 35.14
Librarians ($453,960) (4.00)
School Computer
Technicians
($211,051) (3.73)
Library Paraprofessionals ($15,166) (.27)
Secretaries/Clerks ($754,089) (8.02)
Total ($6,888,215) (42.06)
Total PPE Gap ($2,450)

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The EB model outputs suggest the SMUSD may be $2,450 per pupil short of providing
an adequate education to its students based on its calculations. This only includes staffing and
not the additional dollar resources which are discussed in a later section of the findings. This gap
relates directly to the current and suggested staffing allocations across the district when it comes
to positions within the schools themselves. This metric excludes representation of central office
staff, maintenance and operations, and food services. This gap is quite substantial considering the
exceptional academic performance of the district’s students. Generally, exceedingly high state
standardized test scores like those seen in the SMUSD suggest that most, if not all, students are
receiving an adequate education. In some ways, this per pupil expenditure gap suggests the
SMUSD has found effective ways to use resources to maintain a high level of academic
achievement. It should also be noted that this result includes all of the SMUSD’s revenue
sources, including the parcel taxes and schools foundation grants and contributions.
The first critical finding occurring in Table 9 is the gap in revenue and FTE for
instructional coaches. Odden and Picus (2020) cite empirical research that contributes to the
credibility and effectiveness of enrolling instructional coaches at the site level. These authors
suggest, through the EB model, allocating one full time instructional coach for every 200
students (see Table 4 in the review of literature in this study). Notably, the EB model suggests
that the SMUSD should add an additional 12 FTE of instructional coaches totaling well over one
million dollars. The SMUSD currently has an allocation of zero instructional coaches, potentially
making the recommendation of 12 by the EB model the only coaches in the district if it were
implemented. There are one or two teachers on special assignment, but their responsibilities
include administrative functions, such as program management and accountability. The lack of
resources invested in instructional coaches presents an interesting phenomenon. Where the
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literature clearly outlines the benefit of instructional coaches, a district with exceptional
academic performance formally allocates no resources toward their use. It might be the case that
the district and community value class size over the implementation of instructional coaches as
these coaching positions would remove a teacher from the classroom to perform coaching duties,
thereby potentially increasing class size but also improving student performance, according to
the literature.
Table 4 in Chapter 2 suggests that for K-3 the class size be 15 students to 1 teacher and
for 6-12 the class size be 25:1. Table 9 shows the SMUSD to be nearly 33 core teachers short,
totaling almost four million dollars in cost. Ed-Data (2019) reports the pupil-teacher ratio to be
19.5 pupils to 1 teacher during the 2018-2019 school year, .5 lower than the county average. This
data is a representation of all certificated FTE in the district. A clear conflict emerges here as Ed-
Data suggests the class size to be within the recommendation of the EB model. However, the EB
model suggests that the SMUSD is falling critically short of meeting the class size suggestions.
This discrepancy might be explained by certificated staff members who are not working as
classroom teachers in the district as well as the specialist and elective areas having lower than
recommended class sizes. While it is true that the majority of the parcel taxes and SMSF pays for
people and positions over materials and technology, it does not come close to fulfilling the
suggestions of the EB model. In the context of California, the SMUSD provides relatively low
classes according to Ed-Data which shows the pupil-teacher ratio to be 19.5:1 during the 2018-
2019 academic year, with 6th grade likely being the closest in adherence to the model proposed
by Odden and Picus (2020) in Table 4 of this study. Throughout the remainder of the discussion
and investigation of the findings, this core teacher shortage will appear worse at some levels than
others.
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The results for elective and specialist teachers depict a less substantial gap. This could be,
in part, due to the strength of the visual and performing arts (V APA) programs at the middle
school and the vast array of electives offered at the high school, including three foreign
languages. The SMUSD prides itself on offering highly specialized and sought after programs.
The near conformity to the EB model in this area also reflects the local politics. V APA and
certain foreign languages, such as Chinese and Japanese, are important offerings for the SMUSD
to accommodate the large Asian population as well as the more entrenched, affluent white
demographic that exists. Furthermore, in a geographic location with several long standing and
successful, prestigious private schools, elective courses and programs prove to be an area where
the most innovation and uniqueness can be cultivated. For the SMUSD to only have a seven
teacher deficit as opposed to a 33 teacher deficit in the core indicates that the SMUSD may be
allocating resources to the specialist and elective teacher pools over the core. There is political
risk in the decision to dedicate more resources to the core instructional program, however, as
nearby private schools tend to trademark themselves on unique and longstanding V APA or arts
programs.
When it comes to the SPED instructional program for the SMUSD, the EB model
actually suggests that the district employs one more teacher than the model estimates. The
SMUSD contains a much smaller SPED population than many of its state counterparts (see Table
5 for SPED student demographic percentages in the SMUSD). It should also be noted that a great
deal of funding for the SPED program comes from the federal government through the IDEA and
its policy prescriptions. Odden and Picus (2020) prescribe a certain number of SPED teachers
per 1,000 total students in a school to serve all SPED students. This may, in part, be taken from
and aligned with federal IDEA policy for SPED funding. In terms of the three major teacher
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groups in the model: core, elective or specialist, and SPED, the SPED program tends to align the
most with the EB model, suggesting that SPED students in the SMUSD are resourced at an
adequate level.
Within the EB model output, instructional and supervisory aides are separated into
different line items. In their text, Odden and Picus (2020) discuss these two classifications
synonymously. The authors make clear that there is a body of educational literature supporting
the use of instructional aides as long as they meet certain criteria. Specifically, these aides must
be highly trained in a specific intervention or tutoring program that they can effectively
administer the program to students. In many contexts, however, these aides tend to spend most of
their time fulfilling duties and responsibilities teachers may not be able to complete. I did not
include an extensive survey of what duties instructional or supervisory aides are performing, in
reality, at all of the school sites, making the extent to which aides in the SMUSD align with what
Odden and Picus (2020) recommend unclear. According to the allocations in this area, the district
is overstaffing this position by 13 FTE, or approximately $700,000. Moreover, the district is
underfunding the supervisory aide classification by 7 FTE. The EB model does not support the
implementation of instructional aides when they are used to support teachers with clerical or
supervisory duties. The research clearly supports the use of instructional aides when they are
highly trained in the implementation of an instructional program they can manage with students.
The findings in this area suggest the district may be overstaffing instructional aides who
are performing duties not in alignment with the research base referenced by Odden and Picus
(2020). This could also explain the shortage in supervisory aides according to the EB model.
Instructional aides may be classified as such according to the district, but in reality they may be
functioning in more of a supervisory or clerical capacity. This finding reveals a pattern that is
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likely prevalent across many school districts, but runs counter to an effective use of resources
according to the EB model. Moreover, it becomes natural and organizationally convenient to
have instructional aides perform duties that may run counter to the educational research base. It
takes time, high quality training, and no small amount of discipline to prevent instructional aides
from falling into less effective positions, ultimately spending their time not directly providing
instruction to students or facilitating intervention or tutoring programs for students.
Similar to the instructional and supervisory aide implementation, the EB model
champions a very strong tier one instructional model with highly effective classroom teachers
that can provide high quality instruction to a vast and diverse learner base. It is for this reason
that the EB model favors the inclusion of SPED students in the general education setting to the
greatest extent possible. It becomes a natural observance for many SPED aides to fall completely
into a behavioral supervisor role for students. These aides tend to function in a very limited
instructional capacity. This phenomenon occurs in many public school districts. Program
supervisors and IEP case managers tend to implement the use of aides as an intervention. The EB
model makes very clear that at every possibility, students with Individualized Education Plans
(IEPs) should be fully involved in the general education environment to the maximum extent
possible. These findings suggest that the SMUSD, at a 35 FTE SPED aide surplus, is
misallocating these resources. Furthermore, it must be noted that this surplus in FTE and revenue
is coming from funding specifically tied to the district’s SPED program. Neither the SMSF nor
parcel taxes fund positions tied to the SPED program in the district. It is unclear how many of
these aides are enrolled to support moderate and severe cases on SMUSD campuses. As a broad
interpretation of these findings, one could suggest that SMUSD could cut the number in half and
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save approximately $1,000,000 to allocate toward more classroom teachers or instructional
coaches, assuming the funds were not restricted in any way.
The EB model indicates a shortage of both librarians and school computer technicians for
the SMUSD. As Odden and Picus (2020) state, school computer technicians largely operate out
of the central office, which would not be reflected in this data. Central office staffing relative to
the EB model is outlined briefly in a later section of the findings. This pattern holds true for the
SMUSD. While the EB model shows a shortage of technicians, the district does employ three
FTE school computer technicians. Of more importance is the identification of a shortage of four
librarians, one for each school site in the district. Odden and Picus (2020) explain the evolving
role of the librarian in the 21
st
century learning environment. The SMUSD enrolls some library
paraprofessionals as termed by the EB model to perform some duties generally performed by full
time librarians. It should be noted that the district staffing data does not allocate a formally
labeled librarian in its data.
Furthermore, with steady but significant declining enrollment impacting the district,
renovations to libraries have not been prioritized by the school board or district administration to
the point where any modernization or inclusion of technology has occurred. The district’s
libraries appear outdated which leads to a lack of student engagement and time being spent in the
libraries. In essence, it could be gathered that the SMUSD is not meeting an adequacy standard
for its students when it comes to the maintenance and attention to both the physical library space
and its staffing needs. As stated previously, however, these students have clearly demonstrated
that the library may not be a pivotal factor in whether or not they achieve success as measured by
state performance tests.
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Overall, this broad district data helps to establish patterns that appear more vividly or in a
more obscure fashion at each school site. Two prevailing patterns across the sites are a lack of
use of instructional coaches as well as an over allocation of resources to both SPED and
instructional aides. When it comes to core and specialist teacher gaps, these are far more
apparent at the elementary and high school, with the middle school coming the closest to meeting
the ratios prescribed by the EB model. In most respects, the patterns illustrated by the district
wide EB model output are shown at each individual school site, however, as the findings detail,
some schools have drastically more aligned resource models than others when measured up
against the EB model.
Table 10 pertains more specifically to the second research question of the study. When
looking at Table 10, the reader can clearly see the significance of the other locally generated
revenue when it comes to certificated FTE. Without this revenue, the school district would have
a drastically different instructional model that includes an intensely higher class size. The two
most notable columns to compare are the FTE allocations in the LCFF column alongside the
parcel taxes and SMSF. At the secondary level, more of the FTE is funded through parcel taxes
and the schools foundation rather than the LCFF. The SPED certificated FTE metrics carry less
significance in this context and in the study overall as this program is federally funded. To be
clear, SPED certificated staff do not include aides. This study and its findings focus solely on
locally generated revenues as well as state funding through the LCFF.
The examination of specific staffing resource allocations in the SMUSD illustrates one
aspect of the narrative in the district as it relates to school finance adequacy. The sum of all
revenues in the SMUSD when placed next to the EB model show quite a substantial shortage of
resources. The second research question driving the study revolves around implications of such
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findings for the SMUSD and its process of allocating resources. Table 10 assists in unpacking
these implications. This table shows more of the LCFF funding being spent at the elementary
levels with a much higher ratio of other locally generated revues going to the secondary level.
Much of the declining enrollment in the district occurs at the secondary level. Students leave the
district for private options beginning in the middle school, with much more pronounced
declining enrollment occurring at the high school level beginning in ninth grade.
The SMUSD likely allocates these parcel tax and foundation revenues to the high school
level to demonstrate to the community the efforts it is taking to retain and attract students.
Indeed, relative to California, but not the EB model, the SMUSD maintains a low class size, with
the parcel tax and SMSF revenue performing most of the heavy lifting in terms of resources.
When one considers what the SMUSD might look like without any of the parcel tax or schools
foundation revenue, it becomes immediately apparent that the classrooms and class sizes would
look dramatically different. At the middle and high school, more resources funding certificated
staff come from other locally generated revenues as opposed to the core LCFF grant provided by
the state of California. If these other sources of revenue are taken away, it effectively cuts the
number of teachers at least in half at the middle and high school level, drastically changing the
quality and effectiveness of classroom instruction. It is also worth briefly noting the nonexistent
role Title I funding plays in the SMUSD.

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Table 10
2020-2021 Certificated SMUSD FTE by Revenue Source
Location

Funding Source
LCFF SPED Title I Parcel Taxes; San Marino Schools
Foundation
Total
Valentine 17.1 3.8 0 12 32.9
Carver 17.7 4.8 0 12 34.5
Huntington 8.7 6.9 0 20.4 36
San Marino High 16.7 5.9 1 33 56.6
Total 60.2 21.4 1 77.4 160

Revenue Differences and Staffing for the SMUSD High School
The following section outlines findings specifically related to San Marino High School.
At each level, the findings will, in part, reflect the district findings. However, each level also
does have distinct outcomes that deserve acknowledgement. In many areas, the high school
reflects small gaps in relation to the EB model’s recommendations. Table 11 outlines the EB
model’s outputs in the form of a gap analysis specifically for FTE and staffing. The table
includes both certificated and classified findings as laid out by the EB Excel model. In total, the
EB model shows the high school to be roughly 13 FTE short of providing an adequate education
to its students based on the EB model. The finding correlates with a close to two-million-dollar
revenue gap.

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Table 11
Evidence-Based Model Gap Analysis for High School FTE and Total Revenue
Position All Current SMUSD Revenue FTE
Principals $0 0.00
Assistant Principals ($82,484) (0.59)
Instructional Coaches ($426,722) (3.76)
Core Teachers ($1,007,791) (8.88)
Specialist Teachers $162,699 1.43
SPED Teachers ($85,319) (0.75)
ESL Teachers ($27,238) (0.24)
Academic Extra Help Staff ($261,784) (2.31)
Non-Academic Pupil Support $69,910 0.62
Nurses ($144,057) (1.27)
Extended Day/Summer
School Staff ($68,094) (0.60)
Instructional Aides $84,956 1.50
Supervisory Aides ($71,262) (0.95)
SPED Aides $460,122 8.12
Librarians ($113,490) (1.00)
School Computer Technicians ($89,864) (1.59)
Library Paraprofessionals ($4,909) (0.09)
Secretaries/Clerks ($259,440) (2.76)
Total ($1,864,718) (13.12)
Total PPE Gap (1,959)

The total revenue gap correlates to a $1,959 per pupil resource gap for the students at San
Marino High School. Half of this shortage comes in the form of core teachers. The identified
core teacher FTE gap provided by the EB model is almost nine teachers, or just over one million
dollars in revenue. This core teacher shortage is a prevailing finding at all levels, with the middle
school coming closest to matching the EB model recommendation at six core teachers short. The
other finding that occurs through the district is lack of use of instructional coaches. While the EB
model supports the implementation of instructional coaches, the SMUSD does not employ any.
This finding might suggest that instructional coaches may be more useful in a district with a
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different demographic as students in the SMUSD achieve exceptionally high academic scores on
state standardized assessments without the use of coaches.
An area where the high school slightly exceeds recommendations by the EB model is in
the area of specialist teachers. These teachers are responsible for teaching electives and those
courses lying outside of the core subjects of English, math, and science. The school is currently
about one and a half teachers over the recommended allotment of specialist teachers by the EB
model. As the district continues to face declining enrollment, the specialist teaching positions
face potential reductions in order to preserve the core instructional program positions. In the past,
the community of San Marino has rallied to find funding through the SMSF to fund these
positions, with clear expectations that the district will use the funding to employ specialist
teachers, particularly in the area of VAPA. In sum, it has largely been the community’s desire to
use the specialist or elective area of education to provide prestige, uniqueness, and options for its
students.
The last resource area deserving of note falls in the purview of special education. As
pointed out in the overall district findings, the district over spends on SPED aides. This finding
appears at each level of the district, but is most pronounced at the high school and middle school
level. This finding signifies a trend in the IEP process occurring at these levels that is either
known and supported or unsupported, or entirely unknown. Case carriers are either assigning
aide support in IEPs at a rate accepted by district leadership, or, this pattern may not be visible to
district leadership. This finding could have significant implication for district leadership in how
they provide resources. However, once aide support is implemented in an IEP, those funds
become a part of a federal program with strict requirements and accountability.
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In sum, the high school in the SMUSD falls clearly short of the prescriptions of the EB
model. The school is a microcosm of the image the district portrays when aligned with the EB
model. Patterns apparent in the district findings clearly appear when looking at the high school in
isolation. Taking the resources that are currently within the support of SPED aides and
distributing it to other areas, such as a librarian, instructional coaches, and academic extra help
staff would bring the high school closer to adequacy as outlined by the EB model. The largest
indicator, however, for the high school, is the one million dollar shortage in core instructional
program teachers. While simple, this prevailing finding costs the most money and people for the
district and far outweighs any other shortages the EB model outlines.
The single SMUSD high school employs the highest ratio of locally generated revenues
in the district, with only 16.7 out of a total 56.6 certificated FTE being funded by the state’s
LCFF as outlined in Table 12. Parcel taxes and the SMSF provide approximately double the
revenue that the LCFF does. With a critical shortage of core teachers when applying the sum of
revenues in the district, it becomes almost baseless to imagine what San Marino High School
would look like without the 33 FTE provided by the parcel taxes and schools foundation. Entire
programs would be cut along with an unfathomable increase in class sizes. This school
demonstrates the outward manifestation of the community of San Marino putting its affluence
and financial volume to employment in the single public high school in the area. The goal to
stand out and compete with the local private schools and other high performing public school
districts has led to an unrecoverable reliance on the community’s willingness and ability to
provide financial support through the foundation and renewal of parcel taxes.

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Table 12
2020-2021 Certificated High School FTE by Revenue Source
Location

Funding Source
LCFF SPED Title I Parcel Taxes; San Marino Schools
Foundation
Total
San Marino High 16.7 5.9 1 33 56.6

Revenue Differences and Staffing for the SMUSD Middle School
The middle school in the SMUSD provides the closest alignment to the EB model’s
recommendations. It is the most adequately funded school in the district. In terms of overall FTE,
it resources more than what the EB model recommends at 1.2 FTE over. Moreover, an overall
revenue gap remains. While the middle school shows an overage of 1.2 FTE, it also shows a
$634,341 revenue gap. This finding indicates that there are adequate FTE at the school, but it
may not be allocated appropriately. This revenue gap results in a $967 per pupil expenditure gap
for the middle school. This PPE gap, in comparison to the high school’s $1,959 PPE gap,
indicates a much more substantial level of resourcing. Table 13 illustrates the gap analysis
summary output performed by the EB model using current FTE allocations and revenue for the
middle school in the SMUSD.

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Table 13
Evidence-Based Model Gap Analysis for Middle School FTE and Total Revenue
Position All Current SMUSD Revenue FTE
Principals $0 0.00
Assistant Principals $76,235 0.54
Instructional Coaches ($372,247) (3.28)
Core Teachers ($776,272) (6.84)
Specialist Teachers $289,626 2.55
SPED Teachers $266,420 2.35
ESL Teachers $41,991 0.37
Academic Extra Help Staff ($218,784) (1.93)
Non-Academic Pupil Support ($226,980) (2.00)
Nurses ($99,266) (0.87)
Extended Day/Summer
School Staff ($44,450) (0.39)
Instructional Aides $152,920 2.70
Supervisory Aides ($200,479) (2.67)
SPED Aides $812,029 14.34
Librarians ($113,490) (1.00)
School Computer
Technicians ($15,607) (0.28)
Library Paraprofessionals ($25,927) (0.46)
Secretaries/Clerks ($180,062) (1.92)
Total ($634,341) 1.2
Total PPE Gap ($967)

Table 13 provides the basis for exploring some key findings specific to the middle
school. First, there is an even greater overage of elective or specialist teachers at the middle
school than at the high school at 2.55 FTE over the EB model prescription. This equates to
nearly $300,000 in revenue that could otherwise be redirected at FTE for the instructional core or
at instructional coaches, which, like the high school and throughout the district, reflects zero
current allocation. The overall core teacher resource gap for the middle school follows the high
school and district as a whole, falling nearly seven FTE short with a revenue gap of nearly
$800,000.
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The area of SPED shows over allocation for both teachers and aides. The SPED aide
finding is most pronounced when viewing the overall district gap analysis data. This could mean
that the district is currently having to use a portion of the general fund LCFF grant to pay for
aide support offered by case carriers in students’ IEPs. While it may be a growing phenomenon
for public school districts to have their SPED resource demand encroach on their LCFF general
fund, for the SMUSD this poses a more serious threat. With a substantial core teacher and
instructional coach shortage, it makes reallocating resources even more difficult as SPED aides
and teachers are oftentimes tied to IEPs which are federally binding documents with substantial
accountability measures.
These shortages in the area of core teachers and instructional coaches directly countered
by the overallocation of resources in SPED signify one of the significant policy
recommendations mentioned later in the study. The district and high school data, along with the
currently presented middle school data, suggest that resources should be redirected from SPED
aides and instructional aides into coaches and core teachers. This finding supports a core tenant
in the literature supporting the EB model. Odden and Picus (2020) suggest that every effort
should be taken to fully mainstream students with disabilities, which would translate into a very
sparing assignment of SPED aide support. The current EB outputs suggest that the SMUSD,
most notably at the middle school, has placed over $800,000 in SPED aide support that might be
better spent in instructional coaches aimed at developing teachers to be able to support and tailor
general instruction to be more encompassing and inclusive of a learner base that includes
students with mild or moderate disabilities. In fact, the resources from SPED aides more than
covers the gap in instructional coaches for the middle school specifically.
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While the middle school demonstrates the smallest gap in resources when placed next to
the EB model, some overall district patterns are still evident. There is a substantial core teacher
gap, a slight overage in specialist teachers, and a somewhat counterintuitive allocation of
resources in SPED aides. Table 14 demonstrates a less severe reliance on local revenue
generation than the high school, but also portrays the near equality of FTE allocation from the
LCFF and SPED revenue source. In many scenarios, the LCFF should far outweigh what might
be allocated from SPED as the SPED population in a given school should be vastly smaller than
the general education population. In the SMUSD however, much of the general education
resources are complemented and reinforced by the substantial local revenue generation in the
form of the SMSF and parcel taxes.
Situated in similarity to the high school, it becomes almost baseless to consider the
instructional context of the SMUSD middle school without the support of these local revenue
sources. The middle school employs less of the local revenue generation than the high school
because it plays a slightly less critical role in combatting declining enrollment for the district.
Even so, the middle school maintains a unique elective and specialist teacher makeup with full
time art, band, choir, and orchestra teachers. Declining enrollment for the district begins in
middle school, but does not begin critically impacting the district until high school. The
elementary schools show an almost reversal in revenue sources for the district, further supporting
the notion that the local revenue generation is largely employed at the secondary level to combat
declining enrollment.

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Table 14
2020-2021 Certificated Middle School FTE by Revenue Source
Location Funding Source
LCFF SPED Parcel Taxes; San Marino Schools
Foundation
Total
Huntington 8.7 6.9 20.4 36

Revenue Differences and Staffing for the Two SMUSD Elementary Schools
The first critical factor to consider when examining the findings for the two elementary
schools is that these figures do, naturally, cover two schools while there is only one high school
and one middle school presented in the other tables. While resource and FTE gaps may appear
larger in the elementary findings, it must be noted and reviewed that these findings cover two
schools in a district that shows resource gaps in most areas. The elementary findings show an
overall FTE shortage of just over 30, with an overall revenue gap of $4,389,216. This ultimately
results in a PPE gap of $3,649 for elementary school students in the SMUSD.

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Table 15
Evidence-Based Model Gap Analysis for Elementary School FTE and Total Revenue
Position All Current SMUSD Revenue FTE
Principals $0 0.00
Assistant Principals ($94,669) (0.67)
Instructional Coaches ($569,152) (5.02)
Core Teachers ($1,947,488) (17.16)
Specialist Teachers ($1,229,324) (10.83)
SPED Teachers ($60,367) (0.53)
ESL Teachers ($37,452) (0.33)
Academic Extra Help Staff ($383,975) (3.38)
Non-Academic Pupil Support ($140,879) (1.24)
Nurses ($182,038) (1.60)
Extended Day/Summer
School Staff ($67,148) (0.59)
Instructional Aides $528,140 9.33
Supervisory Aides ($291,192) (3.87)
SPED Aides $717,867 12.67
Librarians ($226,980) (2.00)
School Computer
Technicians ($105,581) (1.86)
Library Paraprofessionals $15,670 0.28
Secretaries/Clerks ($314,587) (3.35)
Total ($4,389,216) (30.15)
Average Gap Per School ($2,194,608)
Total PPE Gap ($3,649)

The most expensive shortage for the elementary schools, in alignment with the other two
schools, is in core teachers. However, given the substantially smaller size of these schools, a 17
FTE core teacher shortage gap, or roughly eight per elementary school, signifies a much more
substantial gap in resources. Unlike the high school and middle school, the elementary schools
have large specialist teacher gap of almost 11 FTE and $1.2 million. Within the community of
San Marino, investments in VAPA programs provide a strategic combat tool for declining
enrollment. The local revenue generation goes entirely to these programs at the secondary level,
which supports the overage both of those schools show, even in relation to the highly resourceful
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EB model. For the secondary level to over allocate in specialist teachers but so clearly fall short
in core teachers further reveals the community’s dedication to supporting programs like VAPA
to match local private schools and other affluent public school districts.
The prevailing SMUSD pattern of over resourcing aides is present at the elementary
school but does not only showcase an overage of SPED aides, but also instructional aides. The
over allocation of resources to instructional aides more than doubles the combined amount of
both the middle and high school. The EB model shows a surplus of over $500,000 in
instructional aides and more than $700,000 in SPED aides. Reallocating both of these figures
would cut the overall revenue gap for the elementary schools by over 25%. The instructional
coach shortage also manifests at the elementary level with similar impact.
While the middle and high school show a large portion of their revenue sources to come
from the schools foundation and parcel taxes, the elementary schools revenue sources indicate
the opposite. The majority of certificated FTE at both elementary schools comes from the LCFF,
returning to a more traditional public school revenue source structure. Nearly a third of each
school’s certificated FTE comes from other local revenue generation. The findings provide the
last data driven finding that supports the community’s heavy investment of their financial
contributions into the secondary level, placing less value on early childhood education than
competing for student enrollment by supporting prestigious and unique elective programs like
VAPA and maintaining relatively low core class sizes at the secondary level. While the EB
model suggests lower class sizes at the elementary level, 15:1 specifically at the K-3 level, the
students in the SMUSD have historically performed far above average on state standardized tests
despite the most significant core teacher shortage occurring at the elementary level. Table 16
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outlines the funding sources for each elementary school, sorted by the LCFF, SPED, and other
local revenue sources, specifically the parcel taxes and SMSF.

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Table 16
2020-2021 Certificated Elementary School FTE by Revenue Source
Location

Funding Source
LCFF SPED Parcel Taxes; San Marino Schools
Foundation
Total
Valentine 17.1 3.8 12 32.9
Carver 17.7 4.8 12 34.5

Dollar Resources for the District
The overall dollar resource gap for the SMUSD is small, totaling only $83 per pupil. This
finding marks a clear contrast from the staffing gap outlined by the EB model in prior sections of
the findings. Table 17 outlines the specific comparisons between the SMUSD and EB model
recommendations. Of note in Table 17 is the instructional materials and assessment category as
well as the GATE category. These findings signify that, broadly, the SMUSD is providing its
students with an adequate education according to the EB model, however, other areas of these
findings suggest under allocation in certain areas. The categories show no pattern, with areas
demonstrating a clear gap and instructional materials and assessment far exceeding what the EB
model provides. In fact, every area indicates a shortage of funding other than instructional
materials and assessment.
The greatest gap for the district is in technology resources. A variety of phenomena likely
are responsible for this finding. First, none of the local revenues provided by the community
provide encouragement to spend on resources other than teachers to lower class size or provide
specific programs. Second, much of the teaching staff in San Marino is veteran. Generally
speaking, teachers who grew up using technology in the recent past are more likely to employ its
use and benefits in their classrooms. Much of the SMUSD teaching force has not required any
substantial investment in technology to supplement the instructional context. Furthermore, given
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San Marino’s affluence, there likely isn’t a demand for access to technology in the school setting
as most students have access at home. While Odden and Picus (2020) do not formally endorse
heavy investments into technology such as the 1:1 model, the EB model does still prescribe a
significantly larger investment in technology than the SMUSD currently provides. Lastly, given
the SMUSDs need to compete with local affluent districts and private schools, not much revenue
is left to allocate toward technology as such significant amounts are allocated in people and
support staff.
The largest gap in favor of the SMUSD is in instructional materials and assessment. This
further reflects the district’s preference to invest in materials over technology. It is common
practice in the district for teachers to innovate and employ new curricula quite often. This is
where the majority of these expenditures come from. This finding also likely reflects the
seniority of the certificated staff in the district. Additionally, there has traditionally been less
pressure on teachers and schools in the district to address the achievement gap with investments
in technology as the students have ritually performed far above the standard. If the district
enrolled students from more diverse socioeconomic and racial backgrounds, the resource
allocation might favor technology more than instructional materials and assessment. The
combined allocation of resources by the district in technology and instructional materials and
assessment equates to the sum of resources prescribed by the EB model for this area specifically.

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Table 17
SMUSD Allocation and EB Model Recommendation for Dollar Resources
Category Current SMUSD
Allocation
EB Model
Recommendation
Difference
Professional Development $159,319 $351,375 ($192,056)
Technology $260,998 $702,750 ($441,752)
Instructional Materials and
Assessment $1,187,326 $604,365 $582,961
Student Activities $774,454 $843,300 ($68,846)
GATE $0 $112,440 ($112,440)
District Total $2,382,097 $2,614,230 ($232,133)

Outdoor Education at Huntington Middle School
The outdoor education program at Huntington Middle School deserves further analysis as
an outlier, in some ways, of resources relative to the rest of the district. This program far and
above requires more resources than any other within the SMUSD at either the primary or
secondary level. All three grade levels at the middle school attend week-long outdoor
experiences at grade level specific destinations. In total, this program costs well over $300,000
every year. This more than doubles the cost of athletics and student activities for the school. As
considered an activity by Odden and Picus (2020), this program alone contributes to the gap
having a relatively small margin for the district at $68,846. Without the middle school’s outdoor
education program, the district would reflect a much larger resource gap around student
activities. This program is a trademark of the SMUSD local affluence, as these resources come
entirely from the local community. No state allocated LCFF funds are used for this program.
Furthermore, every student at the school is given the option to attend, with attendance data being
well over 90%.
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Gifted and Talented Education (GATE)
Findings in the area of GATE for the SMUSD appear straightforward but demand
explanation and placement in the greater picture of this high performing district. There is no
formally identified resource allocation for GATE in the SMUSD. Odden and Picus (2020)
associate GATE students with achieving above state proficiency standards. The majority of
students in the district perform far above the state proficiency standards in both ELA and math.
According to the California School Dashboard (2017) students in the SMUSD are performing
nearly 100 points above the standard while the rest of the state is performing only 2.5 points
above the standard. The same margins are apparent for math according to the California School
Dashboard. In this way, much of the student population in the SMUSD is, relative to the other
millions of students in the state of California, gifted and talented. Furthermore, Odden and Picus
(2020) outline some level of resources that are needed to identify low income GATE students
using performance assessments and other tools. The SMUSD enrolls very few, if any, low
income students, so a sizeable resource allocation for this subgroup may represent less of a
priority.
Aside from the more objective explanations for the lack of a formally labeled allocation
of GATE resources at the school sites in the district, there is also a great political influence
associated with academic programs that, in any way, stratify students. While a GATE program,
done correctly, should benefit all students as a result of better trained teachers and more
equitable outcomes, the political landscape in SMUSD would likely problematize the use and
application of GATE resources. There is an embedded priority within the San Marino
community to stand out academically. This is due, in part, to the long tradition of academic
excellence supplied by the district but also due to the nature of declining and enrollment and the
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unique geographic location of the district in its proximity to so many prestigious private schools,
such as Harvard-Westlake.
District Office
The EB model outlines suggested staffing for a district’s central office based on
enrollment. Table 18 displays the EB model’s outline for a district with 3,900 students, an
adjusted suggestion based on this ratio using SMUSD enrollment, and also SMUSD’s current
allocation at the central office. These findings hold extra significance for the district as many
district positions were cut after the 2019-2020 school year to stabilize the district’s financial
state.
As seen in Table 18, the current SMUSD allocation indicates an over allocation of
resources within the district office. Adjustments for enrollment show the SMUSD to have
approximately six administrators with around 11 classified staff. Currently, the district uses
seven administrators and almost 20 classified staff. Despite significant staffing reductions in the
district during the prior academic year, the EB model shows modest over allocation of resources,
particularly in the classified area. According to the current allocation of resources at the district
level, there is not one particular department with an oversized staff, rather it appears the district
allocates an extra FTE or two spread out across departments.
Table 18
SMUSD Allocation and EB Model Recommendation for Central Office Staffing
EB Model Ratio EB Model Recommendation Current SMUSD Allocation
3,900 students 2,811 students 2,811 students
8 administration 5.76 administration 7 administration
15 classified 10.8 classified 19 classified

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Maintenance and Operations
Resource allocation when it comes to maintenance and operations is calculated and
situated differently than certificated and other classified staffing and dollar resources when it
comes to the EB model. Yet, similarly, Odden and Picus (2020) use the same base of research in
their creation of ratios and calculations related to adequate staffing resources for this area of an
educational organization. The EB model dictates suggestions for 1) custodians, 2)
groundskeepers, and 3) maintenance workers.
Custodial
Table 19 displays the EB model’s ratios for calculating an adequate allocation of
custodial staff as well as the findings for custodial staffing in the SMUSD. Similar to the district
office, maintenance and operations staffing data reveal an over allocation of resources in this
area according to the EB model. The district currently allocates roughly four more custodians
than suggested by the EB model. These findings likely reflect the local politics and demand for
exceptional aesthetics by the community. Given the affluence and wealth of the local area and
community involvement, it makes sense that the district would heavily invest in the cleanliness
and orderliness of its restrooms and waste management.
Table 19
SMUSD Allocation and EB Model Recommendation for Custodial Staffing
EB Model Recommendation Current SMUSD Allocation
1:325 students 1:216 students
1:13 teachers 1: 9.61 teachers
1:13 classrooms 1: 9.61 classrooms
9.29 total custodians 13 total custodians

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Groundskeepers
Table 20 illustrates the ratios for calculating groundskeepers. Calculations for this
position are similar, however, it is built upon using number of schools as opposed to numbers of
students, teachers, and classrooms. Relative to the EB model, groundskeeper allocations in the
district reveal near alignment. Like the custodial staffing allocation, the physical school sites of
the SMUSD are well-maintained and visually appealing. The local politics and expectation of the
community of its schools to be exceptionally maintained in their presentation are reflected in the
district’s allocation of groundskeepers. Furthermore, the district allocates these resources in
efforts to compete and slow the pace of declining enrollment. Nearby private schools employ and
compensate teams of groundskeepers and other staff as a way to entice parents to enroll in their
schools. The small over allocation of groundskeepers for the district almost surely reflects this
environment of competition with local private schools.
Table 20
SMUSD Allocation and EB Model Recommendation for Groundskeeper Staffing
EB Model Recommendation Current SMSD Allocation
.25: 1 elementary .41: 1 elementary
.5: 1 middle .66: 1 elementary
1.5: 1 high school 1.66: 1 high school
2.5 total groundskeepers 3 total groundskeepers

Maintenance Workers
The last of the positions supplied by the EB model under the category of maintenance
and operations are maintenance workers. The EB model suggests using the following elements to
calculate the number of maintenance workers: number of buildings, gross square footage,
enrollment/1,000 students, and the general fund revenue. These numbers are all added and an
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average is taken to produce the adequate number of maintenance workers according to the EB
model. The limitations section in chapter five outlines further discussion as to why only
enrollment/1,000 was used to analyze this area of staffing. Table 21 displays the staffing outputs
and current allocations for the SMUSD using the enrollment/1,000 element only.
Unlike custodial and groundskeepers, the maintenance worker allocation in the SMUSD
falls almost an entire FTE short. These findings may reflect the overcompensation of resources
for maintenance and operations in custodial and groundskeepers. The district, in addition to
needing an FTE for a maintenance worker, has many HVAC and maintenance-related systems
that are old and outdated. As an example, the middle school recently completed a brand new
gymnasium complex complete with a fitness room, brand new locker rooms, and a spacious
multipurpose room. These resources from the community resulted in an investment to signify
competition and exceptionality. Classroom ventilation systems, as unveiled by the COVID-19
pandemic, reveal outdatedness and incompatibility with newer, more effective air filters. In the
field of maintenance and operations, however, it is common practice for organizations to
underfund the maintenance and upkeep of systems such as HVAC.
Table 21
SMUSD Allocation and EB Model Recommendation for Maintenance Staffing
EB Model Recommendation Current SMUSD Allocation
Enrollment/1,000 Enrollment/1,406
2.811 total maintenance workers 2 total maintenance workers

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Food Services
Odden and Picus (2020) explain that, in general, food services departments in public
school districts are self-sustaining, not producing significant amounts of revenues to contribute
to other areas of the educational landscape, but not requiring any major investment from the
organization from the general fund. In the SMUSD, the food services follow this pattern. It
should be noted in the findings, however, that the district has absorbed the majority of the cost of
food services staffing and operations in the 2020-2021 school year due to COVID-19. This is
because students are not attending school and purchasing lunches. The district has set up times
and locations to disperse lunches in a drive by style program. The lunches being sold are not
covering the cost of food services operations and staff as they normally do in a traditional on
campus instructional model which has caused the district to provide resources to continue
employing these individuals and allowing their operations to properly function.
The core EB Excel model does not provide space to input food services allocation levels
due to the fact that, as stated above, this department is generally considered a neutral financial
branch of a school district. This also explains why there are no discussed ratios, formulas, or
suggestions from the EB model in the present section of study’s findings. I investigated the
historical trend of resource allocations for this department and discovered that, apart from the
uniqueness of the COVID-19 pandemic, SMUSD food services generally sustains itself without
creating additional sizeable revenue or expenditures for the district.
Impact of COVID-19
The COVID-19 pandemic has caused social, economic, and political turmoil on a global
scale. When the virus made its way to formal recognition requiring public health action in mid-
March of 2020, it created anxiety and stress for the entire field of education. Schools closed and
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district leaders entered a period of dealing with forced change and adaptation on a new and
unique level to most. In the context of public education in California, and for the SMUSD
specifically, the COVID-19 pandemic has had a relatively minimal impact on its financial
standing. In the present environment and in some ways, the pandemic has proven to be a
financial stabilizer in some ways for the SMUSD. Of course, the pandemic has had critical
impacts on the instructional and social-emotional status of students, staff, and the greater
community not just in San Marino, but across the world.
Traditionally, public school districts in California are funded using a measurement of
Average Daily Attendance (ADA) that is taken multiple times a year by the state. The LCFF
provides funding for every student using ADA and additional weights for students that belong to
certain demographics, such as low socioeconomic and English Learner designations. See Table 3
in the review of literature for an example of a weighted per pupil funding formula. This is the
core principle behind the SMUSD not receiving any additional LCFF funding from the weighted
metrics of the formula; the district enrolls virtually no students belonging to what the LCFF
defines as supplemental and concentration grant demographics. As a result of the COVID-19
pandemic, the state of California made the policy decision to fund public school districts for the
2020-2021 school year with the same ADA measurement from the 2019-2020 school year. In
essence, this means that public school districts did not suffer any immediate financial distress
during the 2020-2021 school year, where the large majority of the data used for this study comes
from. If student enrollment experienced growth during the 2020-2021 school year, that ADA is
not currently factored into their main LCFF grant.
For school districts like the SMUSD and many others that are in a consistent state of
declining enrollment, they likely received a larger ADA grant than they would in the normal
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circumstances because they likely are not seeing a growth in student enrollment. The ADA in
these districts is likely lower than it was during the 2019-2020 school year, but the state of
California is funding the district with that school year’s ADA, not the 2020-2021 school year.
The state of California has also announced it will be funding the 2021-2022 LCFF grants using
the 2019-2020 ADA. For the SMUSD, this means that the immediate effects of COVID-19 on
the financial health of the organization are likely to come later, with losses being seen during the
2022-2023 school year or later and lasting a few years.
Conclusion
An overall pattern of resource allocation in the district indicates a substantial gap at the
school sites in the certificated area, with certain schools showing far more pronounced resource
deficits relative to the EB model than others. For other dollar resources, the district showcases a
resource gap, but not nearly as pronounced as the certificated staffing gap as demonstrated by the
EB model. Certain programs like the outdoor education program at the middle school represent a
heavy investment and legitimate gap closer for the district, but also reveal a lack of broad
resource allocation in student activities across the district. Most pronounced in terms of findings
between overall revenues and resource allocation in comparison with the EB model are found in
the lack of use of instructional coaches, a large shortage of core teachers, and either an over
allocation or mis allocation of aides at all levels. For district office staffing, maintenance and
operations, and food services, findings indicate an overallocation of resources in these areas
aside from food services. For review, food services, according to historical district data, is self-
sustaining. Overall gaps in the central resources related to student achievement are most
pronounced at the elementary level, with the high school in the middle, and the middle school
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showing the closest alignment with the EB model’s prescription of staffing allocation in the
SMUSD.
A critical objective of the study is to understand the extent to which other locally
generated revenues, aside from the LCFF, factor in to the appropriateness with which the
SMUSD provides its students with an adequate education relative to the EB model prescriptions.
Tables 10, 12, 14, and 16 outline the allocation of resources by revenue source in an organized
fashion that present to the reader the difference in resources allocated at the district level and
then at each individual education level within the district related to FTE staffing. Overall, it is
clear that the cumulative revenue generated by the district falls substantially short of the EB
model prescription. When considering a reality without the parcel tax and schools foundation
revenue, it becomes clear that the SMUSD would look remarkably different, particularly at the
secondary level where more than half of the certificated FTE is resourced from these specific
revenues. A clear narrative emerges when considering why these resources become more
centrally located at the high school level as students matriculate through the district. The
SMUSD and its local community has invested substantial resources to combat declining
enrollment in a way that the LCFF will never provide. The struggles the SMUSD faces are not
outlined as priorities for the LCFF and its policy purpose. The EB outputs, local revenue
generation, and LCFF allocations reveal that the SMUSD faces a challenge objectively not meant
to be solved by the LCFF. The LCFF, as contextualized in the literature review through the
tracing of school finance litigation efforts, is designed to redistribute resources to poorer areas,
not supplement affluent districts in their attempts to combat declining enrollment for reasons
largely associated with materialistic wealth and demonstrations of affluence and prestige

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Chapter Five: Summary, Conclusions, and Implications
The SMUSD, for its uniqueness in terms of revenue generation, reflects a great history of
the development of school finance, particularly how resource allocation has changed over the
decades. As a district in a real estate-affluent area in California under the Local Control Funding
Formula (LCFF), the per pupil funding formula, as shown in this study, contributes to the
creation of a far from adequate education for this district’s students. As mentioned in the review
of the literature, however, adequacy is generally defined as an educational organization’s ability
to resource schools to levels that provide every student the opportunity to meet the state’s
established academic performance standards. Students in the SMUSD achieve far above the
average relative to the rest of the students in the state on state standardized tests. In summary, the
community of San Marino, while leveraging an array of other locally generated revenues, still
falls far short of providing an adequate education based on the Evidence-Based (EB) model, yet
still has a student population demonstrating they are receiving an adequate education according
to performance on state standardized tests. As a researcher, I believe this speaks to the
complexity around creating policy that can reliably steer student achievement on a very broad,
perhaps national, level. Several factors ranging from parent involvement, state legislation, local
politics, school finance litigation, shifting demographics, equity and social justice initiatives, and
quality of professional development all play essential roles in determining the quality of learning
and instruction in the classroom.
Purpose of the Study
This study ultimately aimed to determine the extent to which the SMUSD provides its
students an adequate education based on the EB model of school finance adequacy. Further, the
study attempts to elucidate some of the uniqueness revolving around the SMUSD’s local revenue
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generation and its relationship with both the LCFF and EB model’s suggestions. The per pupil
expenditure level provided by the LCFF is low relative to similar districts with very high levels
of poor, minority, and other marginalized groups given its location in an extraordinarily affluent
real estate market. This is not only a reflection of the weighted per pupil funding formula
working as intended, but also a clear example of the progress and change around school finance
from the early 1900s to the present day.
Summary of the Findings
The findings of the study have demanded most attention and analysis in the area of full
time equivalent (FTE) allocations. Table 22 outlines total FTE from the LCFF, parcel taxes and
SMSF, and the EB model. It is important to note that Table 22 does not display SPED and Title I
funding. These two sources are embedded in to the total SMUSD FTE column of Table 22. The
study focuses on the extent to which the SMUSD provides its students an adequate education
using the LCFF and other locally generated revenues. Further, it investigates the implication of
those findings for the use and application of resources in the SMUSD. The findings ultimately
place the district into a relatively unique position in the overall context of school finance
adequacy.
The SMUSD faces significant problems that do revolve around funding; however, these
problems are fundamentally different than the ones the LCFF subscribes to solving. The LCFF
and the larger pathing of school finance has moved in a direction of equity, coming up with per
pupil funding formulas and centralizing resources at the state level to redistribute and subsidize
resources for students who have been identified as needing more. While officials of the district
may also cite a lack of equity for their students in receiving relatively less LCFF funding than
neighboring affluent districts, this type of equity is not the same as the type set out to be
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conquered by the LCFF and other per pupil funding formulas across the nation. The EB model
provides a few key patterns that can help the district to move in a direction of providing a more
adequate education to its students with the resources it currently has to manage. Table 22
ultimately showcases the lower proportion of LCFF funding the district uses to resource its
people, the abundantly high amount of other locally generated revenues the district employs, and
the prescriptions of the EB model of school finance adequacy. While the SMUSD falls short
even in its application of all revenues, the EB helps to point out where the SMUSD and
California as a state measure up. If one of the more affluent school districts in the state does not
meet the standard of adequacy while employing several million dollars of other locally generated
revenues, one begins to imagine how this single district reflects the state’s overall position in
quality of public education resourcing.

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Table 22
Total FTE Comparison by Revenue Source with Overall EB Model Revenue Gap
Level FTE Revenue
LCFF Parcel Taxes;
SMSF
Total SMUSD FTE EB Model
Elementary 49.375 24 96.32 126.46 ($4,389,155)
Middle 12.65 21.4 57.29 56.08 ($634,341)
High 23.05 32.5 73.54 85.65 ($1,864,718)
District Total 85.075 77.9 227.15 269.19 ($6,888,215)

District Findings
The district findings show the most significant shortage relative to the EB model in the
provision of core teachers across all school sites. Further, the findings indicate an overallocation
of resources to aides, particularly those in SPED. This is matched by an equally critical under
representation of instructional coaches. These two findings when considered together create a
promising policy initiative for the district. However, the question over its value remains as the
students of the district have long achieved at remarkable academic levels, presumably without
the use of instructional coaches. For the district as whole, the findings suggest a critical
dependence and reliance on the local revenue generation for any hope of providing an education
competitive with its local rivals in private schools and other affluent public districts.
Elementary Findings
It is clear that the community and district have decided to employ the use of local
revenues to support the secondary level. The elementary findings show the majority of its
staffing to be provided by the LCFF, with critical shortages in both core and specialist teachers.
The elementary level is the only level where the proportion of state received funds outweighs
those of locally received funds. Further, the elementary level is the only one not meeting or
exceeding the prescription of specialist teachers by the EB model. Like the district and secondary
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schools, the pattern of not employing instructional coaches and over allocating resources to aides
is also on display.
Middle School Findings
The middle school findings showcase a clear emphasis on resource allocation over either
the elementary or the high school. It is the only school to net an FTE allocation more than the EB
model prescription. Even so, it still displays a shortage in overall revenue, indicating a misuse of
resources in particular positions. This is most clearly seen in a large excess of resources spent on
SPED aides. Furthermore, it shows the largest net overage on specialist teachers, demonstrating a
clear emphasis on providing an array of specialist and elective options for its students. Given the
middle school’s use of the outdoor education programs as well as its staffing outputs, it becomes
clear that the district either purposefully or unintentionally places the most value at the middle
school in terms of resource allocation. This may be purposeful as the beginning of the secondary
level begins to display increasing levels of declining enrollment as students are getting older and
beginning to purposefully situate themselves to gain entrance to the most prestigious universities
and postsecondary opportunities.
High School Findings
The resource landscape at the high school demonstrates the triumph of the community
but also the precariousness of the future for the SMUSD. While it does meet the EB model’s
recommendation for specialist teachers, it falls substantially short of the core teacher provision.
Further, the overwhelming majority of certificated FTE are funded through local revenues,
particularly the parcel taxes and schools foundation. Should there ever be a political wrongdoing
on the part of the district that causes the community to vote down the parcel taxes, the school
risks undergoing a monumental transformation. The high school maintains the same district
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pattern around instructional coaches and SPED aides. A critical juxtaposition of the high school
and elementary schools and the revenue sources of certificated staffing reveal that the high
school maintains the heaviest level of dependence, by far, on local revenue generation. Further,
there is less of an overallocation on aides than at the elementary or middle level, signifying that
there is less resources to be redirected to reflect a more adequate education. Overall, the high
school represents the largest gap when compared with the EB model, but also the least amount of
misallocation of resources. Not only do the middle school and elementary schools have more
resources than the high school to reallocate in more effective areas according to the EB model,
they rely less on the parcel taxes and schools foundation than the high school to operate.
Limitations of the Study
The portions of the study centering on FTE and staffing have very few limitations. There
are clear allocations of FTE for each site and at the central office. Furthermore, it is very clearly
documented which source of funding supports each FTE. The largest portions of a public school
district’s budget are allocated to staff. In this way, the study very accurately and objectively
demonstrates the current allocation of human resources versus the EB model’s recommendations
which use objective enrollment and student demographic data. While staffing and human
resources make up the significant portion of a school financial context, the other metrics
measured in the study termed “dollar resources” by the EB model are not as clearly defined and
allocated. More significantly, the way these resources are labeled by the SMUSD accounting
office rarely aligned precisely with the EB model’s descriptors and classification of resources.
Dollar Resources
The data around dollar resources required by the EB model fall into five separate
categories: 1) professional development, 2) technology, 3) instructional materials and
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assessment, 4) student activities, and 5) gifted and talented education. The SMUSD accounting
office data does not clearly align with these categories in their financial documentation.
Naturally, the district does allocate resources in these areas, however, in many instances, the
specific account number correlated with an item required in the EB model includes other items
not necessarily categorized in the same place as the EB model. Ultimately, the SMUSD allocates
resources using different categories of classifications of resources than the EB model requests.
To account for these discrepancies, I spoke informally with district and site personnel to
come up with reasonable percentages for resource allocation based on professional judgment and
historical spending where these misalignments occurred. Specifically, this type of percentage
calculation was used for student activities at both the elementary levels, and professional
development for all four sites. In other instances, such as with technology, the figure that ended
up making its way into the EB model for official use almost entirely matched up with the
requirements of the EB model, or it was determined that any other resources included in the
account would have minimal effect in its skewing of the resource allocation in question.
Professional Development
Calculating the appropriate current level of resource allocation for professional
development as outlined in the EB model brought unforeseen challenges to the study. Odden and
Picus (2020) provide costs associated with professional development as teacher time, trainers
and coaches, administration, materials, equipment and facilities, travel and transportation, and
tuition and conference fees. SMUSD’s organization of financial data, while relatively aligned
with these costs for professional development, included an array of additional items not fitting in
to the parameters of professional development outlined by the EB model.
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To investigate and ultimately move forward with a reasonable figure for professional
development, I consulted with the director of accounting, assistant superintendent of business, as
well as site administration to create a percentage of the overall district professional development
account to be input into the EB model. The percentage used to calculate the $159,319 was taken
by first examining the total dollar amount in the district’s professional development account then
multiplying it by 10%. The 10% figure was concluded as being most reasonable given the
parameters outlined in the EB model.
Technology
Managing the limitations around technology involved different strategic adaptations on
my part. I added up all accounts most closely aligned with the parameters outlined in the EB
model. Furthermore, the overall cost associated with technology does not have formal allocations
at the site level. To appropriately determine technology resource levels for each site, the total
technology allocation was determined for each school site by dividing the amount into per pupil
cost. The total technology amount was divided by overall enrollment to determine a per pupil
cost for technology, then multiplied by each school site’s enrollment to arrive at a cost for
technology by school. It should be noted that the only cost associated with technology that may
have meaningfully fell outside of the parameters of the EB model were some heating, ventilation,
and air conditioning (HVAC) costs embedded in technology accounts at the district level.
Instructional Materials and Assessment
Instructional materials and assessment included a core, few accounts at the SMUSD. Like
technology, however, these costs are aggregated at the district level, with useable figures at the
site level not painting the full picture of this area of resources needed by the EB model. The
expenditures in the SMUSD measured up largely with the EB model. Odden and Picus (2020)
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lay out textbook and curriculum materials as being the most significant costs in this area of
resources in the EB model. This is reinforced in the SMUSD data, however, some of the
accounts associated with these costs also mention some maintenance and operations supplies in
the same accounts that provide resources for instructional materials and assessment, similar to
the limitations associated with technology expenditures. The findings indicate an overallocation
of resources for instructional materials and assessment. The costs associated with maintenance
and operations are certainly responsible for some of the overallocation as Odden and Picus
(2020) do not include maintenance and operations supplies as appropriate for instructional
materials and assessment. I was unable to gain more specific access to organize and disaggregate
the specific expenditures in this area. Furthermore, Odden and Picus (2020) reference the
investment in formative or interim assessments. The SMUSD minimally reflects any investment
in this area.
Student Activities
For both the high school and middle school, calculating student activities resource levels
included a process almost entirely in alignment with the EB model, however, at the elementary
level, I faced more challenges. At the elementary level, the allocation for student activities is
intertwined with other categories of spending. This may be due, in part, to the lack of a central
Associated Student Body (ASB) program. For the secondary level, all activities are largely
processed through an ASB account, making it efficient and clear for the purposes of entering it
into the EB model. To arrive at a meaningful student activities figure for the study, I consulted
the financial site summaries for both elementary schools as well as with each respective principal
to determine a percentage calculation of the overall school site allocation that would be
acceptable for student activities. While Table 17 only outlines overall district levels, 25% of each
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elementary school’s overall school site allocation was used for each elementary school Excel
input in the EB model.
Gifted and Talented
The category of gifted and talented education (GATE) reflects a zero dollar amount for
the district. One reason for this figure comes from the lack of any formally identified GATE
resource allocations in the district, at any school site. The presence of a formal GATE program in
the SMUSD is attached to political and social factors that may make the implementation of a
GATE program problematic. Given the attention and heavy investment of parent resources in the
district, a GATE program may only serve to further stratify or group students and increase
political tension among parents that students ultimately must bear the cost of. As reviewed in the
study, most students in the district achieve far above average scores on the state’s standardized
test in both ELA and math. In some ways, the district enrolls large number of academically
gifted and talented students.
Odden and Picus (2020) explain that a sizeable portion of a district’s GATE program
comes in the form of an investment in assessments to identify GATE students who also fall into
a diverse set of demographics, including low socioeconomic and minority. The SMUSD does not
employ the use of any assessment programs to identify and differentiate for GATE students.
While it may have been possible to extrapolate loosely connected resources dedicated to
identifying exceptional or talented students in the district, I elected to err on the side of rigor in
terms of collecting and inputting financial data into the EB model. I do not include prerequisite
placement test costs as a GATE resource as these are largely teacher developed, and the amount
of accelerated or advanced courses sometimes outnumber the level of standard courses at the
secondary level.
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District Office
Odden and Picus (2020) provide ratios and staffing allocations based on enrollment for
district office staff. For the SMUSD, whether or not an employee was considered classified or
administration is clearly designated with the exception of two positions: a district nurse and
director of accounting. The district nurse is compensated the same as a certificated teacher, but is
responsible for coordinating health services for the entire district. Because this position holds a
human resources designation formally different from that of a classified employee, the position
was included in the administration allocation for the purposes of this study. Furthermore, there is
no formally labeled administrator or designated director for health services for the district.
The director of accounting position also required some decision making on my part in
terms of whether or not the position should be considered classified or administration. I decided
to enroll the director of accounting position into the administration group. First, there is an
executive director role of curriculum and instruction clearly labeled as a part of the
administration in the district. The director of accounting role, while not an executive director,
does not have another equal in the district among classified position titles. More clearly, there are
no other directors among the classified group in the district. Because the director of accounting
maintains a supervisory status with multiple employees and is charged with a great deal of
responsibility in maintaining compliance and transparency in financial accountability for the
district, I decided to include the position among the administration, rather than the classified
employee group.
Maintenance and Operations
The EB model, in calculating resource allocations for maintenance and operations,
requires knowledge and data around gross square footage and building counts. In my discussions
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with the district administrators, these figures are not readily known. As a result, I used the
prescribed EB model’s formulas, compensating for the lack of square footage and building count
variables. Given this limitation, the staffing allocations may not reflect full fidelity with what a
formal EB model output might produce. It must be noted, however, that these ratios and formulas
involve multiple variables and factors to calculate outputs in the areas of groundskeepers,
maintenance workers, and custodians. In every case aside from maintenance workers, the
majority of variables were accessible to me. Findings and implications around this area of the
study are still interpreted and discussed despite this limitation.
Policy Implications
This study reveals some objective and broad policy-based factors that impact the SMUSD
and its resource landscape. The chief factor revolves around the design and purpose of the LCFF.
This factor happens to not assist the SMUSD in its challenges and should not be considered by
the district in the future as a potential asset. The policy prescriptions of the LCFF include no
attempt to assist the SMUSD in battling with its unique set of problems. Further, the gradual
centralization of public school funding and the creation of relevant per pupil funding formulas at
the state level occur as a way to further an agenda of equity and resource redistribution to poorer
and more disadvantaged areas. The area of San Marino will likely never be a poor area that
inhabits sizeable groups of poor students and minority students, particularly Latino and black
families.
On the other hand, the district currently invests resources in ways that do not align with
the EB model of school finance adequacy. A repurposing of some resources may allow the
district to further support students as they continue to excel academically. Additionally, a
community call to invest in areas like libraries may also create more engagement and social
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growth for students in the district. The local politics the district wrestles with and the local
revenue generation are likely factors to heavily contribute to the fate of the district’s resource
effectiveness. A more progressive but likely unpopular policy prescription for the district
involves not only a more purposeful open enrollment program, but one that targets interdistrict
students that award supplemental or concentration grant funding through the LCFF.
Repurposing Aides
According to the EB model, the SMUSD should attempt to repurpose, but even
potentially downsize the use of aides. Odden and Picus (2020) explain that aides should, as
sparingly as possible, be used to support teachers in secretarial or administrative ways as well as
for behavioral supervision, both in the general education and SPED classroom contexts. This
type of organizational adjustment is indeed complex and has implications for a variety of
programs. For SPED, it involves a review of the philosophy and vision for the use of aides as
well an incorporation of other strategies to implement prior to offering aide support in an offer of
Free and Appropriate Education (FAPE). Most significantly, however, it involves a very careful
approach to moving teachers and labor group leadership to understand that the best use of district
resources involves supplementing classroom instruction in the general education environment,
bringing teachers to a point where they can manage academic and behavioral progress without
having to invest in aides. It is appropriate, however, to use an instructional aide that is
specifically trained to administer intervention or tutoring programs to struggling students.
Libraries
While the findings do discuss and present the shortage of formally designated librarians
for each school site in the SMUSD, this policy prescription revolves around a recommendation
to increase renovation and updating for the libraries at each of the school sites, particularly at the
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secondary level. Given the historical and consistent academic accomplishment of students in the
district, it seems fitting that each secondary campus would prioritize the updating and renovation
of a space such as a library. An update of the libraries at each school site would increase student
engagement and connectedness at school. This may add one more variable that could be
associated with the retention of students for the district. The community and district have
investigated resources in many effective areas, and updating and renovating a library, while not
an immediate priority, could prove valuable as a tool for retaining students.
Investing in Instructional Coaches
It may be useful, and in some sense, logical, to consider reinvesting some of the resources
spent on aides into instructional coaches. The district, given the EB model results, could
reasonably repurpose a sizeable amount of extra resources in SPED aides in to closing the
instructional coach gap revealed by the EB model. Much of the policy recommendations around
the area of instructional coaches involve points made in discussing the repurposing of
instructional and SPED aides. Instructional coaches would provide a critical foundation for the
district in moving classroom teachers to a place where they can manage more diverse learners
from the SPED population without having aides in the classroom with students to supervise
behavior. Put simply, the district could move approximately two million dollars in aide staffing
into instructional coach staffing and move significantly closer to providing an adequate
education for its students according to the EB model.
Local Politics
The implications of the influence of local politics will continue to be the most significant
area for the SMUSD district leadership, particularly for whoever fills the role of superintendent.
Given the lack of reliance on the LCFF, the district and its ability to politic with the community
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to secure continued and reliable resources for the purposes of competing with local private
schools will remain its most vital mission. It is critical for the superintendent and board of
education to advertise genuine championship of the school district in local individuals and
organizations. Without the continued support and financial investment of the local community
through parcel taxes and the foundation, the SMUSD would not be able to compete for student
enrollment with nearby private institutions, despite academic achievement.
Parcel Taxes and the San Marino Schools Foundation (SMSF)
These two elements of revenue generation for the SMUSD fill a critical role that cannot
be overstated. Without these two funding sources, the school district would look significantly
different, particularly in its ability maintain the class size it currently applies. Furthermore, these
two revenue sources bring the district significantly closer to aligning with the EB model of
school finance adequacy. The parcel taxes and schools foundation are the objective
manifestations of the school district’s ability to maintain engagement and confidence from the
community. This policy recommendation follows and is married to the recognition of local
politics in the San Marino area. To stay ahead of and secure these resources provided by the
community, the school district should work to move toward a state of permanency in relation to
the security of these resources. For example, the SMUSD should vow to establish a permanent
endowment from the schools foundation and work a permanency clause into the parcel tax
implementation language.
Financial Incentives for Interdistrict Transfers of Underprivileged Students
This final policy recommendation presents the most politically challenging option. Given
the nature of the LCFF and its heavier weighting for students from traditionally underserved
demographics, it would make theoretical sense for the SMUSD to dramatically increase its
119

enrollment of students from these demographics to increase the health and use of the LCFF
general fund. Investments from this new growth of LCFF funding would undoubtedly benefit
students from the appropriate backgrounds, but it would most certainly be the case that the
traditional San Marino student would also benefit in some way from new investments using the
supplemental and concentration grant funding that comes from the enrollment of students with
aligned demographics.
The challenge with this option, however, is the tension with local and traditional politics
in the San Marino area. Historically, the SMUSD is at the apex of state standardized test
performance in the state of California. Not only would enrolling students from underserved
backgrounds initially lower the test scores, but the community would likely protest this policy
move in order to maintain traditional prestige and affluence in their schools. It is already a
cultural practice to place interdistrict students into a category of otherness. The assertors of this
culture include individuals from multiple stakeholder groups from teachers, students, and
community members. Furthermore, this population of students would most certainly not be in a
position to donate to the school district the same way the traditional San Marino family might.
While these students would be generating revenue for the district through the LCFF that it
otherwise would not have, the community likely would not realize or investigate the true worth
of this new diversity of students in comparison to the more direct financial contributions they
provide for the district.
Concluding Comments
The development of school finance as discussed in the review of literature here and in the
allocation of resources in the SMUSD reflects greater, progressive policy and legislation to
create more equitable outcomes for public school students in the United States. The SMUSD also
120

reflects not only where California ranks among its state counterparts in terms of its resourcing of
public education, but also how the LCFF’s weighted per pupil funding formula operates for
districts with very low to virtually no underprivileged student groups. Despite the relatively low
per pupil funding levels in the SMUSD, the students still achieve tremendous academic feats,
sending students to ivy league colleges each year and receiving many students who previously
leave the district for prestigious private schools back due to the higher quality of instruction and
rigor found at San Marino High School.
As the EB model is founded on developing resource allocation levels in relation to state
performance standards, the question around whether or not the SMUSD should receive more
resources despite its demographic of students remains ardent in the San Marino community.
According to a longstanding tradition of exceptional state standardized test performance by
students in the SMUSD, the LCFF would say students at San Marino are receiving enough
resources. Local politics and SMUSD advocates, however, argue that the LCFF works
unfavorably for their district. To maintain the expectations of the community, millions of dollars
in other locally generated revenue is required. Despite the substantial financial investment of the
community through parcel taxes and a schools foundation, the EB model shows a substantial
resource deficit. Students in the SMUSD still continue to perform extraordinarily well, and
larger, much poorer school districts that receive significant LCFF grants continue to struggle in
performances on state standardized tests. Work in the field in concert with academic research
around how resources affect achievement must continue to be adjusted and tuned for clarity and,
most importantly, its translation into public school district budgets and resource allocation
principles and visions.

121

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Abstract (if available)

Abstract This study explores the topic of school finance adequacy by looking at a small, public school district located in San Marino, California. More specifically, the researcher applies one of the four known methods of determining adequacy, the Evidence-Based model, to the district’s current allocation of resources. The researcher inputs a variety of accounting and human resources data points into the Evidence-Based model to generate a side by side comparison of the Evidence-Based model’s suggested resource levels and the district’s current levels of resource allocation. The study also examines the nature of how local revenues outside of the state funding formula are used in the district to achieve more adequate levels of funding for the schools. This quantitative analysis allows the researcher to further understand not only the extent to which the district provides an adequate education to its students, but also the implications other locally generated revenues have on the district’s overall resource landscape. The findings indicate that the district faces an overall resource gap, according to the Evidence-Based model of school finance adequacy. The gap is largest in the area of core teachers. Moreover, findings indicate that the district relies very heavily on other locally generated revenues to function in its current state. The Evidence-Based model results indicate that the district does have some ability to reallocate certain funds in different areas to move closer to providing an adequate education for its students.

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Asset Metadata

Creator Kachold, Ryan Steven (author)

Core Title Investigating school finance adequacy in the San Marino Unified School District

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 04/03/2021

Defense Date 03/12/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag adequacy,evidence-based,OAI-PMH Harvest,resource allocation,school finance

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Larry (committee chair), Hausner, Larry (committee member), Kho, Adam (committee member)

Creator Email kachold@usc.edu,rskachold@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-436032

Unique identifier UC11668090

Identifier etd-KacholdRya-9391.pdf (filename),usctheses-c89-436032 (legacy record id)

Legacy Identifier etd-KacholdRya-9391.pdf

Dmrecord 436032

Document Type Dissertation

Rights Kachold, Ryan Steven

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

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