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Participatory Film-Activism as a Tool for Community Engagement in Circular Economy Transitions: Assessing the Actionable Impact of Films
No full textThe power of documentary films to raise awareness and shape public discourse on sustainability challenges is widely recognized. While documentaries effectively evoke emotions and capture attention, less is known about how they influence societal and cultural discourses. Participatory film-activism builds on the traditional impact documentary format by fostering dialogue and community-driven solutions, engaging viewers in discussions that explore barriers and opportunities for systemic change. My research explored how a participatory film-activism model could serve as a catalyst for engagement in the circular economy (CE) transition, focusing on stakeholder discussions in Santiago, Chile.
I employed a qualitative study, with a nested pretest and posttest quantitative design, using a participatory film activism protocol and critical discourse analysis (CDA) framework consisting of six key stages: pre-survey, film screening, post-survey, facilitated dialogue, CDA, and outcomes reporting. Participants (n = 94) took a pretest prior to watching a screening of a short documentary on plastic pollution. Following the screening, participants completed a post-test. Then, they participated in facilitated dialogue to investigate how stakeholder discourses construct knowledge, what perceived barriers to CE adoption were, and to explore societal attitudes toward sustainability. Participants included university students, small-medium enterprise employees, and government representatives. Qualitative data from facilitated discussions were analyzed through combined inductive and deductive thematic coding using NVivo, followed by
critical discourse analysis to examine language structures, power dynamics, and intertextuality. Quantitative data were collected through pre-post surveys measuring knowledge, attitudes, and behaviors related to CE principles, then analyzed using descriptive statistics, chi-square tests, paired sample t-tests, one-way ANOVA, and McNemar tests.
Results revealed knowledge gaps and behavioral barriers to circular economy engagement, some partially addressed through the film screening alone, according to quantitative analysis. Qualitative discourse analysis surfaced systemic challenges in plastic management, exposed knowledge asymmetries as embedded power structures, and highlighted opportunities for targeted policy interventions. Quantitative data further demonstrated that these asymmetries contributed to power dynamics within CE discourse, with certain groups possessing significantly higher baseline knowledge. However, post-screening shifts in participants’ willingness to engage others suggest that participatory film-activism can function as a meaningful knowledge equalizer and dialogue catalyst. Notably, integrating qualitative and quantitative findings underscores the model’s potential as a scalable, low-barrier tool for surfacing exclusionary narratives, shifting perceptions, and fostering inclusive stakeholder engagement. While structural power imbalances remain challenging to address through education alone, this study provide early evidence that participatory film-activism can play a critical role in advancing community-driven sustainability transitions.Extension Studie
The Origin and Evolution of Search and Rescue Dogs in California
No full textSearch Dogs have been working in California for just over 50 years. They capture the attention and hearts of the public and the media when they respond to help find victims of calamity. And there have been a lot of calamities.
There is no doubt America loves her dogs. While there have been plenty of books that describe individual teams and their exploits in search and rescue, there is very little written work that captures the history and evolution of this profession. Our history is an oral one – passed down from handler to handler, generation to generation. Some is accurate, some is embellished, and some is downright wrong. This research is a labor of love into a profession I have poured my heart and soul into. It deserves to have its founders and innovators highlighted, and a common historical reference established. But mostly, it’s to honor the dogs who are not volunteers, but still willingly go to places most humans fear to tread. They are our partners, our friends, our soulmates, and sometimes our last hope of being found.Extension Studie
"A Government of Men": Responsible Government and the Rule of Law in the Progressive Era
No full textThe Massachusetts Constitution of 1780 famously declares that the principle of the separation of powers will bind the commonwealth, “to the end it may be a government of laws and not of men.” The idea of “a government of laws” expresses the Enlightenment ideal of an impersonal form of rule that substitutes abstract justice for the capriciousness of personal rule and is associated with two distinguishing features of American constitutionalism: the separation of powers and judicial review of administration and legislation. A century after Adams wrote, however, the ideal of “a government of laws” came under attack by a new trend in political thought. In place of a government of laws, a group of turn-of-the-century thinkers that included Woodrow Wilson, Frank Goodnow, Henry Jones Ford, and Herbert Croly advocated a system of government that, by uniting rather than separating legislative and executive power and by reducing judicial control of government, sought to enable an elected executive to hold real responsibility and, accordingly, to be held responsible by voters—what some of them called “a government of men.” Their vision of government was encapsulated in the idea of responsible government. The archetype of responsible government was British parliamentarism, or responsible cabinet government. As theorized and advocated by the American school of responsible government, a range of reform ideas from presidential representation, the unitary executive, and the executive budget, to weakened judicial review of legislation and even, for some, the popular recall of state governor, properly understood, were part of a project to establish some approximation of parliamentary government within the constraints of the American context—what is here called “parliamentarism with American characteristics.” This dissertation offers the first full account of that project.
It does so in six chapters. Chapter 1 begins the story in the 1880s with the idea of formally parliamentarizing the American constitution by giving cabinet members seats in Congress, famously supported by a young Woodrow Wilson but also less famously by Gamaliel Bradford in a modified form. Chapter 2 follows Wilson in his pivot away from the Cabinet-in-Congress idea towards ways of achieving responsible government within the existing system through transformation of the presidency. It traces the development of this idea of responsible presidential government in the writings of James Bryce, Ford, Wilson, and Croly in the context of the transformation of the presidency by the three “progressive presidents,” Roosevelt, Taft, and Wilson. Chapter 3 considers how the principle of responsible presidential government extended from the executive’s leadership of the legislature to its control over the administration in Frank Goodnow’s pioneering scholarship in public administration and administrative law. Chapter 4 extends the analysis to the judicial power by asking just how far the school of responsible government meant to take its critique of a “government of laws” through an examination of the diversity of their views on judicial review of legislation and administration. Chapter 5 situates the school of responsible government in the context of the progressive-era debate over direct democracy and representative government, exploring their varying assessments of the direct primary, initiative, referendum, and recall. Chapter 6 offers an account of the New York Constitutional Convention of 1915, which under the leadership of Henry Stimson synthesized the main principles of responsible government as developed by the figures studied in chapters 1-5 and applied them in a concrete set of constitutional amendment proposals.Governmen
Modeling Delays in Foreign-Backed Infrastructure Projects: A BRI Case Study on Inequality, Corruption, and Governance
No full textForeign Direct Investment (FDI) plays a significant role in global infrastructure development. However, projects funded through FDI often face extensive delays. Using China’s Belt and Road Initiative as a case study, this thesis analyzes which factors most significantly affect the on-time completion of foreign-backed infrastructure projects. Logistic regression models are used to evaluate project completion at various time thresholds. Results show that higher levels of perceived corruption and economic inequality are strongly associated with increased likelihood of delays, while democracy levels in governance have a less consistent effect. Analysis also finds that project-specific characteristics, such as sector and region, also influence delay risk, with projects in the transport sector and those located in Asia featuring fewer time overruns than those in other sectors and regions. These findings highlight the importance of addressing governance and institutional quality alongside technical and logistical planning. By identifying the variables most predictive of delay, this study offers practical insights for planners, investors, and policymakers seeking to reduce time overruns and improve project delivery outcomes in FDI-funded infrastructure.Department of Urban Planning and Desig
Can Large Language Models Make Reading a Book More Engaging?
No full textAmerican literacy is struggling, with only 31% of eighth graders reading at or above grade level. This problem is largely one of engagement: students struggle with reading primarily because they don't read enough to develop proficiency. Poor reading skills lead to avoidance of reading, creating a negative cycle which further diminishes literacy development.
This thesis contributes two novel LLM-based interventions designed to increase student engagement with assigned texts: LLM-Clarifications, which provide just-in-time support when students encounter obstacles while reading, facilitated by a sentence-by-sentence reading mechanism that tracks students' progress and discourages skimming, and LLM-Debates, which allow students to argue with chatbots about characters or themes after reading.
Testing with 63 high school students showed that students equipped with these interventions spent 70% more time engaged with their assigned book compared to the control group and thoroughly read 43% more chapters.
However, comprehension quiz scores increased only by 2.6%. I found that this discrepancy occurs because LLM interventions excelled at sustaining engagement for students who had already begun reading, but not at initiating engagement for students predisposed to skip reading entirely. In both groups, students skipped approximately half of the assigned chapters, with only one student out of 63 reading all chapters without skimming.
These findings demonstrate that the novel LLM interventions successfully solve half of the reading engagement problem: sustaining and deepening engagement once students begin reading. The 70% increase in engagement time and 43% increase in thoroughly-read chapters represent a promising approach to addressing the literacy crisis by keeping students engaged with texts. Furthermore, contrary to some educators' concerns that AI primarily enables shortcuts in education, these results suggest that thoughtfully designed LLM interventions can actually deepen student engagement with learning materials rather than diminish it—providing a foundation for reimagining LLMs as tools that maximize, rather than minimize, students' learning and growth.Computer Scienc
Puzzling Art Market Relationships: Quantifying Provenance to Model Historic Prices of Seventeenth- to Eighteenth-century French Art
No full textPrevious studies of art price modeling relied on RSR, hedonic, or network modeling techniques to interpret a set of variables’ relationship to perceived art prices. There was an adversity in quantifying provenance record as it proved to be a laborious task riddled with limitations in the dataset. Existing research has not analyzed how aristocratic ownership, art dealers, and auction houses interacted within a given network of the art market.
This thesis explores the relationship between provenance and historical seventeenth- and eighteenth-century French art prices in the British and French art market by using a hybrid approach integrating hedonic modeling with network analysis. Using data from the Getty Provenance Index, this study focuses on three provenance indicators: aristocratic ownership, art dealer involvement, and auction house involvement. The key findings supported the importance of auction houses in driving art prices and the heterogenous relationship present within the art market. This work contributes to the growing field of quantitative art market analysis to better understand how art is valued over time.Applied Mathematic
From Tweets to Votes: An Assessment of Twitter’s Role in Donald Trump’s 2016 Election
No full textThis study examines how Donald Trump’s Twitter strategy contributed to his victory in the 2016 U.S. presidential election. Although Trump’s Twitter activity did not directly secure him the winning votes, it played an indirect role by capturing the attention of traditional media outlets, which then amplified his political messages to a broader audience and ignited voter action. By frequently tagging media networks, journalists, and other traditional media professionals, Trump received substantially more coverage than his opponent, Hillary Clinton, the 2016 Democrat nominee, whose Twitter strategy was primarily targeting prominent politicians and elected officials. This heightened exposure proved critical to Trump’s electoral success.
To support this conclusion, a survey, which generated n=132 responses, was administered. The results indicate that both partisan and independent voters rely more on traditional media for political decision-making than on Twitter content. Moreover, compared to partisans, independent voters are notably less susceptible to being influenced by Twitter in shaping their political views.Extension Studie
Valuation of Solar Asset-Backed Bonds After Issuance: Did the Inflation Reduction Act Lower Spreads Over Benchmark Treasury?
No full textThis paper examines whether Solar Asset-Backed Bonds (ABS) consistently trade at differentiated spreads compared to similar non-solar bonds, reflecting more favorable risk perception and investor willingness to pay a “green premium” for cash flow from solar. There is evidence that spreads on Solar ABS narrowed by approximately 200 basis points relative to non-solar ABS leading up to and during the passage of the Inflation Reduction Act (IRA), a key climate policy of the Biden administration. Despite the initial promising results, however, this study shows that the IRA’s impact on solar ABS waned over time – investors had anticipated more from the IRA and revised their valuations downwards upon realizing its muted impact for residential solar. Spreads widened accordingly, even surpassing non-solar bonds by Q4-2024. However, within the sub-sample of solar bonds, the IRA did have differentiated, sustained impacts on lowering solar lease/PPA spreads by 30-40 basis points relative to solar loan spreads pre-IRA. This demonstrates the significance of the IRA’s tax credit transferability mechanism, which made solar credits refundable for leasing companies, but non-refundable for individual homeowners who had taken out loans.Applied Mathematic
Coordination Under Constraints: A Wireless Signal-Based Framework for Failure-Aware Multi-Robot Exploration
No full textThis thesis presents the WSR Framework, a decentralized framework for multi-robot exploration in environments with limited communication and no shared global map. The system enables teams of robots to coordinate using only onboard sensing and lightweight relative position estimates derived from wireless signal exchanges from WiFi and UWB sensors. Each robot selects exploration targets independently, guided by a utility function that accounts for local information gain and inferred teammate positions. A key contribution is a confidence-based failure detection mechanism that allows each robot to respond to teammate failures using only motion history. The confidence value adjusts how exploration targets are selected, which helps to redistribute coverage progress. The full system is validated through both simulation and hardware experiments. The results show significant reductions in robot overlap compared to zero-coordination baselines, and performance that approaches that of centralized strategies, without requiring explicit communication or shared maps.Computer Scienc
Multi-Persona Oracles for Fair Classification
No full textAs machine learning systems are increasingly deployed in high-stakes domains, incorporating fairness constraints into model training has become a central challenge. Most fairness-aware algorithms assume access to an
idealized human fairness oracle—a source of supervision that is difficult to obtain at scale. Motivated by theories
of value pluralism and drawing on ideas from generative social choice, we introduce the Multi-Persona Oracle
Framework, which uses large language model (LLM) personas to simulate diverse, subjective perspectives on fairness, aiming to more effectively bridge theory with practice.
We collect pairwise fairness judgments from 815 synthetic judges, each representing a unique combination
of personality traits, racial identity, and ideological background. These judgments are elicited using carefully
designed prompts and applied to 200 training and 800 test comparisons drawn from the COMPAS Recidivism dataset. We
extend a no-regret learning framework for fairness-constrained classification, using these constraint sets to train
classifiers and evaluate their generalization across unseen individuals and judges.
We analyze generalization patterns at the level of individual judges, demographically grouped personas, and
two baselines: a default LLM and an expert fairness-oriented persona. To assess robustness, we sweep over a range
of fairness slack parameters γ and report accuracy alongside average and maximum fairness violations on heldout test constraints. In our proof-of-concept case study, our findings show that training on ensembles of judges
yields strong generalization to fairness constraints in out-of-sample holdout sets, due to the complexity of fairness
judgments and the nature of the Logistic Regression model.Applied Mathematic