Jayden Li and research mentor Amarachi Ugwu reviewing work on a laptop
Housing in California:

Policy Portfolio

Li (Jayden) Li
The Thacher School, 5025 Thacher Road, Ojai, CA 93023
jayden.li318@gmail.com
Scroll โ†“

Preface

Addressing Californiaโ€™s housing problems at the forefront of initiative

A resident standing outside a white canvas tent in Ojai's tent village
Figure 1. The โ€œtent villageโ€ of Ojai that retains its homeless population, serving as a transitional encampment until a more permanent project is solidified. Source: Ojai Local Hero

How could a city with so much wealth fail to house its own people, and what can I do as an aspiring policymaker?

Serving as a volunteer delivering food and supplies to homeless shelters and the โ€œtent villageโ€ of Ojai, I met people whose lives contradicted everything I knew about the wealthy town I live ten minutes from. An art student who had lived in Ojai all her life was evicted after mounting debts. A mother explained how incessant price hikes unraveled a decade of stability in her family. In a city where the median home value hovers 210% above the national average, housing affordabilityโ€”and its lack thereofโ€”deeply impacts generations of Ojai locals, compounded by the regionโ€™s ever-increasing housing scarcity and cost of living.

Iโ€™ve delved into policy research and policy initiatives because it turns my helplessness into a method, a field to ask what could be done. By addressing local housing challenges in California, I aim to design solutions for the people in the place I call home.

Contents

01 ยท UC Riverside

โ€œSolutions for the region, solutions for the worldโ€

The UC Riverside Center for Community Solutions (CCS)

The UC Riverside CCS group aims to address pressing public policy questions in Inland Southern California; specifically, my research focused on the Los Angeles and Orange County regions. By providing solutions and services to improve the lives of those in our local region, we can cultivate generalizable knowledge applicable to communities around the world. Through outreach programs and ongoing conversations with community members, industry leaders, and government organizations, I can learn about local issues firsthand and ask policy questions to produce actionable policy within the regional context.

Working with Dr. Qingfang Wang and Kristen Kopko, I serve as the only high school researcher on this team. Through this past year, I have dedicated my time to investigating zoning ordinances across Southern California localities; furthermore, I am working with the city of Riverside to evaluate and implement a new โ€œmissing middleโ€ housing project through contextual policy research, urban planning methods, and a comparative matrix.

Blueprint floor plan of a two-unit missing-middle housing prototype

Compilation of Zoning Ordinances, Los Angeles and Orange County

Purpose

Land codes shape industrial siting, urban density, housing supply, and residentsโ€™ infrastructural welfare. Currently, no rigorous dataset exists that allows researchers to conduct statistical analyses of housing conditions and zoning implementations in these two regions. With the CCS, I created a comprehensive zoning code compilation as an all-purpose resource for future housing policy researchers for the California region.

To build this dataset, I conducted outreach to 125+ municipalities across Los Angeles and Orange County, requesting zoning codes, municipal ordinances, and land-use planning documents that are not readily available online. I compiled raw ordinance texts within Google Sheets into formats suitable for large-scale analysis, standardizing jurisdictional terminology, timelines, and formatting. I also helped pilot AI-assisted extraction methods to speed up data processing, while running manual validation checks designed to catch hallucinated outputs before entries were finalized.

Map of the Los Angeles metro area highlighting LA County and Orange County
Figure 2. The Los Angeles metro area, depicting LA and Orange County. Source: Shay Gilmore Law
125+municipalities contacted
89LA County jurisdictions
35Orange County jurisdictions
Codes availableCodes needing outreachHybrid approach
LA Countyn = 89
29.2%
43.8%
27%
Orange Countyn = 35
28.6%
62.9%
8.6%
0%20%40%60%80%100%
Figure 3. Zoning code accessibility by hosting source across LA County (n=89) and Orange County (n=35) jurisdictions. Data from the authorโ€™s CCS Land Use Policy Tracking Sheet.

Evaluating Possibilities: Missing-Middle Housing in Riverside

Duplex floor plan with three bedrooms per unit
Figure 4. A duplex floor plan made by RADAR as a proposal for missing-middle infill housing in Riverside; total gross area of 1,268 SF.
Aerial view of a vacant lot on Polk Street, Riverside, outlined in red, 102 by 203 feet
Figure 5. Aerial imaging of suitable multi-family unit construction sites. Depicted is Polk St, Riverside.
Purpose

There is a gap in the housing market for small-scale, infill rental and ownership housing, known colloquially as the โ€œmissing middleโ€โ€”housing that falls between a detached single-family home and a large multifamily apartment building. Figures 4 and 5 depict working drafts of missing-middle prototypes and potential locations. Working with local construction nonprofitsโ€”Blended Impact Labs and Parkview Legacy Foundationโ€”and the municipal government, my task was to inform the city of Riverside about policy implications through outreach and data comparison.

Altogether, I conducted outreach to more than 150 municipalities, compiling citiesโ€™ lessons learned on missing-middle projects through a comparative matrix. This matrix provides municipal governments with policy considerations as they move forward with infill housing proposals and construction plans.

Publication ยท UCR Center for Community Solutions ยท 2026 Preapproved Housing Plans for Missing Middle Housing: A Case Study of the City of Riverside The case study my outreach and comparative matrix fed into. In June 2026, the Riverside City Council adopted preapproved plans for two missing-middle prototypes: a duplex and a bungalow that can be arranged around a shared courtyard. Read the case study โ†’

Building the Comparison Matrix

To situate Riversideโ€™s proposal within a broader policy landscape, I compiled and verified data on over 50 comparable missing-middle and pre-approved housing programs, ultimately producing a matrix comparing Riversideโ€™s approach to other California initiatives. This required direct outreach to planning and zoning departments in dozens of jurisdictions to confirm program details, eligibility criteria, and implementation status, including:

Santa ClaraSanta AnaPasadenaSan JoseSacramentoFresnoBerkeleyUnion CityEscondidoEncinitasBeverly HillsBurbankDiamond BarGoletaSonoma CountyMercedWhittierRancho Palos VerdesFairfieldLos Angeles CountyOrange County

Figure 6 depicts the top-down model we adopted for each city:

Program Overview
Jurisdiction
Municipality Type
Initiative Name & Type
Administrative Structure
Eligibility Criteria
Fee Structure
Timeline for Approval
Financing Partnerships
Funding Sources
Institutional Partners
Governmental Partners
Outcome Evaluation
Implementation Status
Noted Challenges
Future Considerations
Matrix categoriesAuxiliary subcategories
Figure 6. A simplified rendition of the policy comparison matrix. Each of the four categories in blue breaks into three subcategories for specificity.
02 ยท UC Santa Barbara

Summer Research Academies

At UC Santa Barbaraโ€™s Summer Research Academies, I enrolled in 93LS Research in STEM. I dedicated four weeks to reading empirical literature, learning statistical methods, and building an original research project under the supervision of Dr. Travis Candieas. Our team focused on the Emergency Rental Assistance Program (ERA) because COVID-19 had intensified the eviction crisis, impacting the housing stability of millions of Americans.

ERA was one of the federal governmentโ€™s main tools to keep tenants housed; we asked whether ERA not only reduced near-evictions but also addressed race- and gender-based disparities in who benefited. To that end, I learned to use R for factor analysis and fixed-effects regression modeling, building measures of housing stability and equity across demographic groups. At the end of the program, we presented our findings to more than 130 students and faculty at UCSBโ€™s Research Seminar, explaining both our policy conclusions and the quantitative methods behind them.

Printed proceedings page: 'Equity at the Edge: Effect of the Emergency Rental Assistance Policy on Perceived Likelihood of Eviction by Demographics' with author photo and abstract
Figure 7. Our abstract on evaluating the ERA, printed in the UCSB Research Seminar 2025 Proceedings.
Research paper ยท UCSB Summer Research Academies ยท 2025 ยท 10 pages Equity at the Edge: Effect of the Emergency Rental Assistance Policy (ERA1) on Likelihood of Eviction by Demographics Alex Kim, Jayden Li, and Matthew Zhang We evaluate whether ERA reduced perceived eviction risk during COVID-19 and whether its benefits reached tenants equally across race and gender. ERA helped near-evicted tenants, but how much depended on race and gender.

Modeling ERAโ€™s Effects

MR1 = โˆ’0.02221 + ฮฒ1dmale + ฮฒ2dwhite + ฮฒ3dAsian + ฮฒ4dother + ฮฒ5dtreatment + ฮฒ6dwhite:treatment + ฮฒ7dAsian:treatment + ฮฒ8dother:treatment
MR2 = โˆ’0.22094 + ฮฒ1dmale + ฮฒ2dwhite + ฮฒ3dAsian + ฮฒ4dother + ฮฒ5dtreatment + ฮฒ6dwhite:treatment + ฮฒ7dAsian:treatment + ฮฒ8dother:treatment
Figure 8. Two fixed-effects regression models estimating the relationship between ERA implementation, race, gender, and latent measures of mental health (MR1) and perceived eviction risk (MR2), with Black women as the reference group.
Model interpretation Using factor scores derived from the Household Pulse Survey, we built two fixed-effects models: mental health (MR1) and perceived eviction risk (MR2). We used Black women as the reference group and compared outcomes before ERA (2020) and after its implementation (2021). Race, gender, and post-ERA indicators measured baseline differences, while race-by-treatment interactions tested whether ERAโ€™s apparent effects varied across demographic groups.
MR1 (Mental)MR2 (Evict)
DemographicsPre-ERAPost-ERAPre-ERAPost-ERA
Blackโˆ’0.022(0.644)โˆ’0.200**(0.004)โˆ’0.221***(<0.001)0.173**(0.011)
White0.235***(<0.001)0.100(0.221)โˆ’0.012(0.819)0.022(0.783)
Asianโˆ’0.195(0.069)โˆ’0.300*(0.045)0.742***(<0.001)0.399**(0.006)
Other0.193**(0.004)0.167(0.194)โˆ’0.060(0.483)โˆ’0.117(0.348)
Maleโˆ’0.184***(<0.001)0.290***(<0.001)
Adjusted Rยฒ0.0480.094
Figure 9. Fixed-effects regression estimates of mental health (MR1) and perceived eviction risk (MR2) before and after ERA implementation, disaggregated by race and gender; Black women serve as the reference group. Coefficients indicate deviations from the reference group, with p-values in parentheses. * p<.05, ** p<.01, *** p<.001.
Key finding There were significant demographic differences: ERA coincided with a lower perceived likelihood of eviction for Black women, our reference group: the post-ERA eviction coefficient was positive (0.173, p=.011). Yet the policyโ€™s effects were not uniform across identities. Black womenโ€™s mental-health score declined after ERA (โˆ’0.200, p=.004); White women reported better mental-health scores than Black women before ERA; and Asian women reported lower perceived eviction risk in both periods. ERAโ€™s benefits were uneven across demographic groups.
Policy implication ERA improved Black womenโ€™s perceived housing stability, but their worsening mental-health outcomes show that eviction prevention alone cannot resolve the manifold dimensions of housing insecurity, including social wellbeing. Future programs should track outcomes by demographic group, reduce language and technology barriers to access, and pair aid with longer-term housing and mental-health support.
03 ยท UC Santa Barbara

Research Mentorship Program

In a continued pursuit to conduct research at the highest level, I enrolled in UCSBโ€™s Research Mentorship Program as a rising senior. Noticing the distinct formation of social enclaves within Santa Barbaraโ€™s various subregions, I posed a question that strived to capture the complexity of policy, social identity, and human behavior:

How do visitorsโ€™ physical interaction with fixtures and spaces in open houses reflect the broader influence of housing policy on social identity?

Conducting over 40 hours of ethnographic research, interviewing real estate agents and prospective buyers in Montecito, the City Center, and Goleta, I tracked behavioral cues and applied grounded theoryโ€”a method of qualitative codingโ€”to 1,000+ interview phrases and observations. In partnership with Amarachi Ugwu, a PhD student from the UCSB Department of Sociology, I authored an 8-page research paper, presented at the UCSB RMP poster session to more than 100 researchers, and presented at the annual Research Symposium to an audience of 130+.

Research paper ยท UCSB Research Mentorship Program ยท July 2026 ยท 7 pages Open House Ethnographies: A Policy-Informed Analysis of Architectural Evaluation Among Prospective Buyers in Santa Barbara Jayden L. Li (corresponding author) and Amarachi Ugwu, UCSB Department of Sociology How open house visitors evaluate architecture amid housing scarcity created by exclusionary policy. Through ethnographic observation and coded agent interviews, the paper argues that housing policy, social need, and everyday interaction with homes are mutually constitutive.
40+hours of ethnographic fieldwork
1,000+phrases & observations coded
130+symposium audience

Policy, Identity, Behaviorโ€”A Mutually Constitutive Cycle

Policy, identity, and behavior operate as a mutually constitutive cycle. Zoning restrictions structure the housing environment and produce measurable patterns of residential sorting. Identity then shapes how people evaluate housing. At open houses, buyers interpret properties through socially produced values about status, safety, family life, and belongingโ€”associations that real estate agents may reinforce.

These evaluations become observable through behavior: where people search and choose to live. Those patterns can reproduce or reveal the consequences of the zoning policies that shaped them.

Policy Identity Behavior
Figure 10. The mutually constitutive cycle theory proposed as the culminating finding of my ethnographic research.
Grounded Theory Raw Data Open Coding Axial Coding
Figure 11. The application of grounded theory, synthesizing the qualitative data collection process so researchers can make sociological and public policy conjectures.
04 ยท Pepperdine University

Rebuilding Public Trust

A literature review for the Pepperdine School of Public Policy

Why do citizens trust, or distrust, the agencies that govern them, and what can institutions do to earn that trust?

Working with Dr. Peter Pirnejad, Dean of Pepperdine Universityโ€™s School of Public Policy, I conducted an annotated literature review on trust in public agencies. My housing research kept returning to the same problem: even well-designed policy stalls when residents do not trust the institutions delivering it. This project let me study that problem directly.

I read and annotated 60 sources spanning more than a century, from Woodrow Wilsonโ€™s 1887 essay on public administration to 2026 Gallup polling. For each source, I recorded its research design, data, central findings, and limitations, covering survey experiments, structural-equation models, historical analysis, and political philosophy. The result is a structured map of what the field knows about public trust and where the evidence is still thin.

The review is now being used to build a new civics course for Pepperdineโ€™s curriculum, giving students an evidence-based foundation for understanding how public institutions earn and lose legitimacy.

Measurement & public-opinion trends17
OECD, Gallup, Pew, ANES, Edelman, GSS, World Values Survey, European Social Survey
Foundations of trust theory16
Levi & Stoker, Pettit, Gambetta, Hardin, Uslaner, Rothstein & Stolle
Public administration & accountability11
Wilson, Friedrich, Finer, Waldo, Appleby, Selznick, Bouckaert
Transparency, performance & local government9
Grimmelikhuijsen, Van Ryzin, Herian, Welch, Van de Walle
Regulation, compliance & legitimacy7
Braithwaite, Ayres, Tyler, Jackson et al.
Figure 13. The 60 annotated sources grouped into five research themes.
60sources annotated for method, data, findings and limits
โ†’
139years of scholarship covered, 1887โ€“2026
โ†’
1new civics course being built from the review

What the Literature Says

72% vs. 1 in 3

In OECD countries, about 72% of people trust the police but only about one in three trust parliament. Trust varies sharply across institutions.

Brezzi et al., 2021
76% โ†’ 21%

The share of Americans who trusted the government in Washington most of the time fell from 1964 to 1994.

Pew Research Center, 1998
Performance โ‰  trust

Good performance does not guarantee trust, but bad performance reliably erodes it.

Bouckaert, 2012
Fairness > force

Tough enforcement had no overall effect on trust in regulators across six countries. Fair treatment is more closely tied to legitimacy and compliance.

Grimmelikhuijsen et al., 2025; Tyler, 2006
5
6
10
11
14
10
Pre-19501950โ€“891990s2000s2010s2020s
Figure 14. Sources by decade of publication (one undated survey source not shown). About half of the sources were published since 2005.
Selected sources
  • Levi, M., & Stoker, L. (2000). Political trust and trustworthiness. Annual Review of Political Science, 3, 475โ€“507. doi.org/10.1146/annurev.polisci.3.1.475
  • Bouckaert, G. (2012). Trust and public administration. Administration, 60(1), 91โ€“115. lirias.kuleuven.be
  • Brezzi, M., Gonzรกlez, S., Nguyen, D., & Prats, M. (2021). An updated OECD framework on drivers of trust in public institutions. OECD Publishing. doi.org/10.1787/b6c5478c-en
  • Grimmelikhuijsen, S., et al. (2025). Does enforcement style influence citizen trust in regulatory agencies? JPART, 35(1), 29โ€“44. doi.org/10.1093/jopart/muae018
  • Pew Research Center. (2025). Public trust in government: 1958โ€“2025. pewresearch.org
05 ยท The Thacher School

Inspiring Local Initiative

The Thacher Public Policy Club

Six club members and guests standing outdoors with mountains behind them
Figure 12. From left to right: Charlie Clarke (Vice President), Juan Sanchez (Faculty Advisor), Mayor Andy Gilman, Jayden Li (Founding President), Paolo McCarrey (Communications), Lucrecia Rodriguez (Member).

To inspire more students to design local solutions and understand the complex housing crisis Ojai faces, I founded the Thacher Public Policy Club (TPPC). TPPC hosts bi-monthly policy seminars that invite students to hold civil discourse on conservation, housing, and zoning policies. Currently, TPPC has educated its 65+ members with the tools to evaluate policy, produce policy briefs, and conduct theoretical research.

TPPC also provides students with a chance to experience how our municipal government operates. Hosting Breakfast with the Mayor, interested students learn firsthand from Mayor Gilman about the operations of the city of Ojai. TPPC also gives students outreach opportunities with Ojai council membersโ€”students have found success discussing their policy initiatives and other partnerships with district representatives and municipal leaders.

68Total club members
100+Hours of policy discussion
4Years of operation

Contact

Portrait of Jayden Li

Phone

(213) 820-6002

Mailing Address

5025 Thacher Rd, Ojai, CA 93023

Email

jayden.li318@gmail.com