VictorJuiz/thesis huggingface dataset:
A principals' principles : tangled hierarchies in charter management organizations
Keywords: Education.

The study of schools as institutions has been central to the fields of sociology of education and organizational sociology long before charter schools started to spread across the US in the 1990s. Since then, business thinking and its related practices have enjoyed unprecedented influence on K-12 schools. Despite thirty years of operations and nearly as much robust research on academic outcomes and community effects, there remains little study of how charter schools are led. I attend to this gap through participant and ethnographic observation across several charter schools and their respective networks, as well as in-depth interviews of charter school teachers and principals, the two most critical positions in schools for student learning. I find tangled hierarchies are endemic to leadership of networked charter schools, where governing boards depend heavily on principals for expertise but rarely grant them autonomy to meaningfully lead, preferring instead they adopt a role akin to that of a middle manager. Principals in a network then are forced to contend, resist, or acquiesce to innumerable decisions of a central office executive staff and their governing board of directors, a process known as managing up. This research has implications for the study of institutions, furthering the notion that they are "inhabited" by agentic actors, but also noting the continuing influence of institutions on organizational behavior. This research also has implications for school leadership and preservice training and education policy, particularly charter schools in noting how the institutional environment of accountability that charter schools bring to K-12 education invariably hamstrings talented leadership
Principled algorithms for domain adaptation and generalization
Keywords: Engineering.

Machine learning models are increasingly applied to datasets different from the training datasets. The performance of models often degrades when tested on unseen scenarios. Empirically, many algorithms have been used for domain adaptation and generalization, but few methods have been able to surpass empirical risk minimization consistently on common benchmarks. Theoretically, traditional learning theory offers limited insights for distributional shift problems. The main goal of this thesis is to bridge the gap between the theory and practice for domain shift problems, and to develop principled algorithms that have better robustness guarantees. We study three domain shift problems with increased supervised from the target domain. We first study domain generalization where no target data is available during training. We show that feature-matching algorithms generalize better when the distinguishing property of the signal feature is indeed conditional distributional invariance. Next, we study domain adaptation where unlabeled target data is available. We show that self-training helps when the target is more diverse than the source. Lastly, we study active online learning under domain shift. We show that uncertainty sampling leads to better query-regret tradeoff when there is hidden domain structure. In all three problems, the synergy of explicit bias from the algorithm and implicit bias from the domain shift structure contributes to successful transfer between domains
Privacy and efficiency in personalized decision-making and recommendation
Keywords: Engineering.

This dissertation explores challenges concerning data privacy and efficiency in decision-making and recommendation systems. The first chapter discusses difficulties of model learning under misspecification in contextual bandits for adaptive decision-making. We propose a reduction of contextual bandits to general-purpose heterogeneous treatment effect estimation, and demonstrate that this approach improves data efficiency and robustness to model misspecification in contextual bandits. The second chapter explores heterogeneous domain adaptation in decision-making in a data-constrained setting. Specifically, we consider learning personalized decision policies on historical observational data from heterogeneous data sources in a federated setting. A federated policy learning algorithm is proposed for this setting and a novel regret analysis is presented that highlights the extent of benefits of heterogeneity in policy learning. The final chapter focuses on data privacy in recommender systems. It proposes a novel approach for developing privacy-preserving large-scale recommender systems with synthetic data generated using differentially private language models. We demonstrate this approach ensures query-level privacy guarantees without sacrificing on recommendation quality, a key step towards the realization of secure and efficient data-driven personalized recommendation
Probabilistic modeling of air and ground vehicle trajectories
Keywords: Engineering.
Aeronautics and Astronautics.

Safe integration of autonomous vehicles into their traffic environments requires modeling human behavior. This thesis presents techniques to model vehicle trajectories that are representative of human driver and pilot behavior in the real world. These models can be used to build simulations for developing and verifying safety-critical traffic systems. Modeling vehicle trajectories can be challenging due to several reasons specific to the context. This thesis presents modeling approaches that address the challenges in each context. For autonomous cars, modeling trajectories can be challenging due to the inherent uncertainty in human behavior and complex interactions among drivers. While a driver model can be learned directly from data, we generally want our models to be interpretable. This thesis addresses this challenge by proposing a framework that combines physics-based driver models with a data-driven learning approach. For conventional types of aircraft, trajectories depend on the flight procedures and instructions from air traffic controllers. In dense airspace, however, aircraft behavior may vary due to factors including the preferences of air traffic controllers and the correlations among multiple aircraft. This thesis proposes a probabilistic model that learns the relation between aircraft and procedures in each flight stage. The trained model then can be used for generating trajectories given unseen traffic environment with procedural information. Further, the thesis proposes a method to incorporate correlations among multiple aircraft. For new types of aircraft such as urban air mobility systems, the major challenge for building models is the lack of available data. This thesis introduces an interactive software package called CONTRAIL, which provides an interface for building an aircraft encounter model by geometrically defining the nominal encounter paths and specifying a probability distribution over the nominal paths. Instead of learning aircraft behavior in a data-driven way, field experts can use this tool to create encounter models and generate realistic trajectories for new categories of aircraft
Probing and designing electrolyte solvation for lithium batteries
Keywords: Engineering.
Materials Science and Engineering.

Capturing anthropogenic carbon dioxide is essential to meet the climate targets.1 Despite the efforts to decarbonize the grid and transportation, some sectors remain difficult to decarbonize, and carbon capture is necessary to reach carbon neutrality.2 The incumbent technology for carbon capture utilizes amine sorbents to scrub CO2 using thermal stimuli suffers from high energy costs; 3 however, the thermodynamic penalty for CO2 capture and release is high and the heating of non-active water solvent with high heat capacity contribute to the high energy cost. As an alternative, electrochemical carbon capture has recently been gaining attention.2 Electrochemical activation prevents energy input into water heating, and also it is possible to achieve high efficiencies by tuning the absorption chemistry. Key prerequisites of candidate sorbents molecules include: 1) low thermodynamic energy cost; 2) facile reaction kinetics; 3) high stability upon oxidation and reduction; 4) preferred compatibility with water.2 In particular, attaining highly stable redox chemistries is a non-trivial challenge, as the redox cycle often involves free radicals. We propose the idea of deploying redox active amine molecules that have been widely deployed in batteries as redox mediators. Redox mediators are molecules that undergo redox cycles to facilitate sluggish reactions at the battery electrode interfaces.4 Because the stability of these chemistries have already been confirmed, and the reaction pathways are well-studied, we believe that they are highly promising candidates for electrochemical carbon capture. Through preliminary studies we have identified a molecule, 4-amino-TEMPO, that stably undergoes reduction and oxidation to capture and release CO2. There are two aspects of this molecule that makes it so promising: 1) it is a stable radical in its native form, making it stable upon repeated cycling; 2) it shows a remarkably small energy cost to capturing and releasing CO2 (Fig. 1). We plan to investigate the capture and release mechanism using a multitude of analytical techniques, including nuclear magnetic resonance spectroscopy (NMR) and liquid chromatography mass spectrometry (LC-MS). In addition, we plan to design a novel flow cell with symmetric reactions (Fig. 2). This should be a breakthrough because all other electrochemical cells for carbon capture have utilized a placeholder reaction on the counter electrode to balance the charge, which calls for additional materials and bulkier setups. We believe that our novel cell design and reaction chemistry will offer an avenue towards practical deployment of electrochemical carbon capture
Probing charge carrier properties in organic semiconductors with optical spectroscopy
Keywords: Engineering.
Materials Science and Engineering.

Polymeric organic semiconductors (OSCs) have complicated, heterogeneous microstructures with significant nanoscale disorder. This thesis broadly shows how spectroscopic characterization via mid-Infrared charge modulation spectroscopy (CMS) and UV-Vis-NIR absorption provide powerful tools to understand disorder effects on electronic charge carriers. The first section shows how CMS spectra can be quantified to yield information on spatial localization of charge carriers, and then this quantification is expanded in the second section to focus on understanding charge transport in a modern, high-mobility OSC. In this section, it is shown that one-dimensional carrier delocalization along polymer chains (intrachain) is sufficient for good electronic charge transport, provided occasional, short-range contacts exist between polymer chains (interchain). Finally, the last two sections focus on understanding charge transport and carrier delocalization in electrolyte gated polymeric OSCs at high carrier densities exceeding one charge per ten monomers. In these sections, the importance of local, short-range intermolecular aggregates on charge transport is explored, and the remarkable result of charge carrier induced structural ordering via increasing polymer chain planarity is shown through a combined spectroscopic and X-ray scattering study. Overall, this thesis broadly shows that intrachain effects appear to dominate charge transport in polymeric OSCs.
Progress and Neglect Within the Same City: Analyzing the Perspective of the Community in Southwest Detroit on Gentrification
Keywords: Gentrification
Urban policy
Belonging (Social psychology)
Text
Thesis

Southwest Detroit, a predominantly Latine neighborhood, is located near Detroit’s rapidly gentrifying downtown area. In response to devastating economic challenges, Detroit has taken a “growth first” approach to revitalization. In the past decade, this approach has become apparent through the city’s focused investments of its limited resources in Downtown Detroit and the improvement of pathways to the business district, such as the construction of the Gordie Howe International Bridge. Drawing on the concept of revitalization as a paradox and the significance of culture and place, I investigate how residents of Southwest Detroit have been affected by these changes and how their sense of belonging and place is affected. I conducted 21 semi-structured interviews to study how residents in Southwest Detroit perceive these changes. The findings of this study suggest that the “growth first” approach results in poor infrastructure outcomes within Southwest Detroit due to disinvestment and exacerbates issues, including legal insecurity, displacement, and pollution. This approach has also brought gentrification to Southwest Detroit, along with a declining sense of belonging and sense of place among Southwest Detroit residents. This study furthers research on the role of gentrification in shaping belonging and attachment to place. Within Detroit, it contributes to expanding conversations about revitalization beyond Black-white relationships by capturing the perspectives of a predominantly Latine community.
Progress towards a total synthesis of the bis-guanidinium neurotoxin zetekitoxin AB
Keywords: Humanities and Sciences.
Chemistry.

Zetekitoxin AB (ZTX) is a potent neurotoxin isolated from the endangered Panamanian golden frog, Atelopus zeteki. ZTX belongs to a family of bis-guanidinium toxins, which includes (+)-saxitoxin (STX) and the gonyautoxins (GTXs). ZTX, however, is ~200 times more potent than STX as an inhibitor of voltage-gated sodium ion channels (NaVs). Two structural features are unique to ZTX: a bridging macrolactam and an unusual guanidinium N,O-acetal. Given that the total isolate supply of ZTX is 300 μg, de novo synthesis of ZTX is the only way to enable structure-activity studies and to confirm the assigned structure. To this end, a route to the tricyclic core of ZTX has been developed to enable access to the natural product. This route also provides access to the related bis-guanidinium toxin GTX.
Project recon : a computational framework for and analysis of the California parole hearing system
Keywords: Engineering.
Management Science and Engineering.

Parole decisions can tip a sentence toward fifteen years or fifty. Despite the great power that parole boards hold, their decision processes are poorly documented and largely hidden from public scrutiny. Parole hearings produce almost no structured data, only an unstructured transcript of hearing dialogue several hundred pages in length. In the following dissertation, we use natural language processing to analyze the transcripts of 35,105 parole hearings held between 2007 and 2019 for candidates serving life sentences in California, totaling approximately five million pages. Through regression analyses of data extracted from the transcripts, after controlling for relevant case factors, we find that several factors outside of the candidate's control explain hearing outcomes. We find that commissioners vary widely in their punitiveness in previously unobserved ways; the assignment to a particular commissioner significantly influences the hearing outcome. Racial disparities limit the quality of legal representation that parole candidates receive as well as their voice in the hearing dialogue, and both significantly predict the parole outcome after again controlling for case factors. Previous analyses of parole systems have been limited by the unavailability of structured data or the task of hand-annotating hearing transcripts. Our results thus provide the most comprehensive picture of a parole system studied to date. While our results carry direct implications for legislative parole reform, our methodology—using machine learning to analyze legal hearings—can be extended to many other procedures in criminal and administrative law with limited structured data
Projection inferences with clause-embedding predicates in RSA models
Keywords: Projection inerences
Clause-embedding predicates
Experimental pragmatics
Probabilistic pragmatics
Text
Thesis

Projection inferences are inferences about speaker commitment to content embedded that project through an entailment-canceling operator. In this thesis, we investigate projection inferences in polar interrogatives with clause-embedding predicates (e.g., Does John know that Julian dances salsa?). Inferred speaker belief regarding whether Julian dances salsa is modulated by multiple factors, including the predicate used, interlocutors' prior beliefs about the content, and the content's at-issueness. In a behavioral study, we investigate the beliefs about contents embedded under the predicates “think” and “know” that listeners ascribe to the speaker and a potential attitude holder (John). We propose three different probabilistic models couched in the Rational Speech Act (RSA) framework, in an attempt to provide a unified computational account of projection inferences about content embedded under clause-embedding predicates. The empirical data are used to infer the parameters and evaluate the model predictions. The predictions of each model mirror some, but not all, of the qualitative empirical patterns. This is a step towards a systematic analysis of projection inferences using probabilistic pragmatic models.
Promoting Equitable Pathways in Engineering and Career Technical Education
Keywords: Engineering Education
Career Technical Education
Equity
STEM
Text
Thesis

My dissertation addresses three studies which ask broadly: What are the predictive metrics of functioning AS-CTE pathways? Can students’ perceptions of these pathways be changed? Are these pathways equitable for female students? In my first study, I take a step toward better understanding the metrics that explain functioning AS-CTE pathways. Through ethnography, I observed that when social mobility was added as a metric of high-quality PBL with AS-CTE in a predictive framework of education success, attendance levels improved. In my second study, I investigated an opportunity gap (Ladson-Billings, 2013) contributing to students’ perceptions that AS-CTE does not lead to advanced STEM degrees. That perception forms a resistance to AS-CTE pathways, hindering efforts to include underrepresented demographics such as women. This study aims to explain to what degree the opportunity gap influences perceptions of obscure high-wage, high-skill careers by youth of an underrepresented demographic. In my final study, I investigated how AS-CTE pathways present barriers to inclusion through hegemonic masculinity (Connell & Messerschmidt, 2005). Building on the work of (Tarantino et al., 2016), this study employs a feminization of PBL mentor intervention to help break down the barriers of hegemonic masculinity in secondary STEM-CTE classrooms. Through ethnographic action research (Hartmann et al., 2009), I found evidence that the humanizing of our VDC-PBL intervention allowed for sites of resistance to gender norms. These studies make three important and timely contributions to the field of AS-CTE and engineering education more broadly. First, I uncover and remediate an ineffective metric of program efficacy, then reveal an opportunity gap which impacts marginalized youth more acutely, and finally I reveal a toxic masculinity within AS-CTE pathways which further impacts those with compounding marginalizations. While uncovering these trends, I offer recommendations to remediate these issues, while also highlighting what is working for these pathways.
Propagule size has context-dependent effects on colonization success in mixtures of gut microbial communities
Keywords:  Department of Biology
Biology
Microbial ecology
Ecology
Text
Thesis

Colonization plays an important role during assembly of the gut microbiome and influences microbiome composition throughout the life of the host, but determinants of colonization success are not yet fully understood. The size of introduced populations and frequency of their introduction can be important drivers of colonization success for introduced species. However, the effect of these factors, which are known together as “propagule pressure,” varies across environments and can be modulated by the strength of competition between introduced and resident species. In vitro microbial communities provide a tractable, high-throughput experimental system to interrogate the influence of propagule pressure on colonization. To quantify the importance of propagule size during colonization in gut microbial communities, we derived in vitro communities from human stool samples and systematically mixed eight pairs of communities at seven ratios ranging from 1:1000 to 1000:1. We compared our results to the predictions of a neutral model in which the relative abundance of each species remains proportional to its inoculation dose, a measure of propagule size. We observed that community co-cultures maintained similar levels of species diversity to the parent communities regardless of mixture ratio, suggesting that community diversity may be limited by resource competition even when many species are initially present. Likewise, community composition was generally maintained across mixture ratios, in contrast to neutral predictions. However, certain bacterial taxa showed varying levels of dose-dependence across mixtures, suggesting that the effect of propagule size depends on community composition and may be affected by the strength of competitive interactions in each mixture. Our results highlight the importance of both propagule pressure and competition in determining colonization success in gut microbial communities.
Punish or Play it Down? China’s Reactions to Border Standoffs with India
Keywords:  Stanford Global Studies
China
India
Foreign policy
Coercion
Content analysis
Text
Thesis

Despite regular border standoffs between China and India since 2012, including one that resulted in deaths in 2020, little research has been done into the specifics of Beijing’s recent foreign policy strategy towards New Delhi. It is time to move beyond studying the border dispute as the dependent variable, and instead situate the border dispute within the broad China-India relationship by looking at standoffs as independent variables that impact China’s diplomatic and economic policies towards India. Using content analysis, I find that standoffs have a moderate negative association with the Chinese MFA’s diplomatic rhetoric, but that during a standoff Beijing continues to portray India in a generally positive light, and often ignores standoffs completely. Additionally, on average the value of China’s imports from India, either in the aggregate or for a few key products, does not dip during or in the immediate aftermath of a standoff, suggesting so far China has not responded to standoffs with economic punishment.
Quantifying and mitigating the contribution of model uncertainty to predictions of the terrestrial carbon cycle
Keywords: Sustainability.
Earth System Science.

The terrestrial biosphere is an integral component of the Earth system, serving as a buffer against the impacts of anthropogenic climate change and providing a wealth of ecosystem services to communities across the globe. However, its behavior and responses to environmental perturbations are challenging to model, mainly due to uncertainties involving model structure and parameterization. Despite a proliferation of targeted model development efforts, persistent disagreement between predictions from different state-of-the-art terrestrial biosphere models hinders the establishment and prioritization of robust management and restoration initiatives. In this dissertation, I develop methods for quantifying and mitigating the role of model uncertainty in predictions of the terrestrial carbon cycle. This was made possible via diverse, multi-scale Earth observations, which I integrate within a flexible ecosystem model--fusion framework. Together, this research provides new insight into the inter-relationship between structural and parametric uncertainties, and also highlights opportunities for using novel data to develop model parameterization strategies that yield realistic variability across the global land surface