VictorJuiz/thesis huggingface dataset:
Learning on the job search : how application experiences shape labor market outcomes
Keywords: Sociology.

Looking for work can be a very fraught experience, filled with immense stress and pressure. The sociological literature, however, has tended to view job searches as simple matching processes, connecting potential employees to employers. In my dissertation, I argue for further interrogation of the job search itself from the perspective of job seekers. In doing so, I highlight the ways in which experiences on the job search come to shape individuals' conceptions about work and about themselves in unequal ways as well as important meaning- and decision-making processes that occur over the course of job search. Drawing on longitudinal interviews with 63 men and women seeking internships and full-time employment in computer science, I find that the actors, processes, and procedures of the job search teach heavily gendered conceptualizations of the field and disproportionately alienate women who were more likely to question their passion for the field and express intentions to leave within five to ten years than their men counterparts. I further show how the processes, actors, and experiences that make up a job search contribute to individual perceptions of competition in the labor market, frequently increasing feelings of pressure and precarity beyond the economic realities of supply and demand. While the impact of this increased pressure was broad, increasing worries and concerns about being competitive enough even among the most privileged job seekers, job seekers with less access to status either through their education institutions or their family class background were more likely to find these experiences played into existing concerns about their belonging in the field. Finally, I additionally examine how job seekers aim to evaluate companies on factors like their diversity and societal impact in the course of a job search, but that doing so is often challenging and ambiguous. Because of this, job seekers frequently considered and applied to companies that they did not feel acted in socially responsible ways and had to manage the tension of seeking employment at firms that do not meet their stated goals. Together, these findings aim to illuminate not just the outcomes but the experience of seeking work in order to begin to unpack the black box of the job search. In doing so, they underscore the unequal and consequential challenges and opportunities that this presents, with important implications for workforce diversity and inclusion as well as the ways in which companies are able to manage potentially negative assessments of their broader social impact
Learning perception and control from rich interactions
Keywords: Electrical Engineering.

Building robotic systems that can perform a wide range of tasks in the real world would require generalizable perception and control. Despite recent advances in deep learning, existing paradigms often rely on extensive human engineering and suffer from limited generalization capability. To handle the desired diversity and complexity in challenging tasks, we would need to further scale up learning by rethinking the methodology for collecting and utilizing data for robots. In this dissertation, we discuss methods that enable robots to enhance perception and control by learning from rich interactions with the environment. We develop structured models and learning algorithms for robots to effectively acquire sensorimotor skills and solve sequential tasks. To scale up learning, we design mechanisms to provide data from various sources. We further propose frameworks that adaptively generate tasks from parameterized task spaces to facilitate curriculum learning and skill discovery
Learning preferences from choices and rankings
Keywords: Electrical Engineering.

A large and growing experimental literature has shown that individual choices and judgements can be affected by irrelevant aspects of the context in which they are made. Despite these findings, much of the existing modeling work in preference learning still relies on the simplifying assumption that choices come from the maximization of a stable utility function. In this dissertation, we discuss our progress in tractably modeling violations of utility-based reasoning in choices and rankings at scale. First, we describe the context dependent random utility model (CDM), our choice model that captures a broad class of context effects while remaining inferentially tractable. Second, we consider testing when violations of a popular notion of rationality, the Independence of Irrelevant Alternatives (IIA), exist in practice. Our work contributes effective methods for testing IIA and characterizes the fundamental statistical limitations of doing so. Third, we show how our advances in choice modeling can be leveraged to develop the contextual repeated selection (CRS) model of ranking, a model that brings a natural multimodality and richness to the rankings space along with strong statistical guarantees
A less thoroughly holistic neobehaviorism
Keywords: Philosophy.

This dissertation begins to explore the philosophical significance of the thesis that some facts about an agent's mind are facts about the agent's abilities. This is done in two parts. First, certain philosophical accounts of knowledge as a kind of ability are discussed and amended with support from original exegetical work on what Ryle calls 'semi-hypothetical' descriptions. Second, an argument is made that certain psychological explanations (of an agent's conduct) underwritten by facts about the agent's knowledge (understood as an ability) are less holistic in a certain way, and consequently that a philosophical Neobehaviorism that incorporates such forms of explanation may be less thoroughly holistic than it otherwise might be
Leveraging bioinformatics methods to examine sex-related variability in genetic and transcriptomic data
Keywords: Biomedical Informatics.

Women are at more than 1.5-fold higher risk for clinically-relevant adverse drug events. While this higher prevalence is partially due to women being overdosed, research suggests that biological sex differences play a role. However, the biological mechanisms behind how sex differences impact drug response are poorly understood. Gene expression and genetic data have the potential to help us investigate these effects, but many studies and samples neglect to include sex labels or examine the impact of sex. Simultaneously, another challenge stems from the overemphasis of certain sex- specific associations without sufficient replication or consideration of other covariates. Consequently, strategic use of data analytic methods is essential for studying sex-related effects. In this thesis, I argue that novel bioinformatics approaches have the potential to improve our understanding of sex as a variable in genetic and gene expression data, and I describe three con- tributions toward this effort. First, I developed a Bayesian Mixture Model approach for identifying sex-specific genetic effects in Genome Wide Association Studies (GWAS). By applying this model to UK Biobank biomarker data, I found that the majority of these clinical lab values do not show sex differences in their genetics, with the exception of testosterone. Second, I addressed the problem of missing sex labels in gene expression data by training models to infer sample sex, and applying these models to over 600,000 publicly available human and mouse samples. I then used these labels to assess sex bias at scale and in drug studies, examine the complexity of cell line sex, and identify mislabeled samples. Finally, I applied our sex labeling models to smoking-related gene expression data, compared the contributions of sex and smoking to expression, and highlighted limitations in our ability to examine sex-differential smoking interaction effects
Leveraging the geometric structure of robotic tasks for motion design
Keywords: Aeronautics and Astronautics.

Robots operating in the unstructured environments of the real world must contend with at least two sources of geometric complexity: (1) the differential geometric complexity of robot configuration spaces and task spaces, which can in practice be general non-Euclidean manifolds, and (2) the complexity of the geometric shape of robot links and obstacles in the environment, which have infinite variability and are often highly nonconvex. Mature robot autonomy requires algorithms that can tackle these sources of geometric complexity with precision and at real-time control and planning speeds. This thesis focuses on bridging existing gaps in previous methods to meet these needs. In particular, to address differential geometric complexity in motion design, we first present a framework called Multi-Task Pullback Bundle Dynamical Systems (PBDS), which is a geometric control methodology for forming fast composable geometric motion policies, respecting simultaneous robotic tasks on non-Euclidean robot and task manifolds. Second, we present an embedded sequential convex programming approach which exploits differential geometric structure to eliminate explicit manifold-type constraints in trajectory optimization while still guaranteeing final satisfaction of these constraints. Together, these approaches correctly enforce the differential geometric structure of robot planning and control problems while maintaining similar or greater computational efficiency compared to past approaches. Finally, we address the shape complexity of robot links and obstacles by repurposing hardware-accelerated ray-tracing (i.e., ray-tracing cores) for rapidly forming collision avoidance constraints in trajectory optimization, particularly targeting complex robot and obstacle triangle mesh representations. This enables robot motion designers to leverage the full complexity of robot and obstacle geometries at speeds orders of magnitude faster than currently available collision-checking libraries, while leveraging recently-developed ray-tracing cores which have previously had little utility in the robot autonomy stack
Lifting the Digital Curtain: Utilizing Social Media to Promote Health Content and Engage with Asian Populations
Keywords: Asian Americans
Asians
Research
Social media
Internet
Ethnicity
Text
Thesis

As our lives become more intertwined with the digital landscape, an increasing number of individuals are relying on the internet and social media as their main sources of health information. Currently, there is a dearth of knowledge on how the Asian community interacts with digital health information, specifically in the context of social media.
In this thesis, a 10-week social media campaign was implemented with the goal of increasing the percentage of Asian participants in the Stanford Research Registry - platforms utilized include Facebook, Instagram, and Twitter through the Stanford Center for Asian Health Research and Education accounts. Participant data was disaggregated by race and ethnicity in order to better understand the diversity among Asian subgroups.
The percentage of Asian participants increased from 14.26% at baseline to 23.83% at the end of the campaign (525 Asian identifying individuals to 1,871). The greatest increase occurred during the General Outreach phase which utilized all channels of outreach available. Frequencies of Japanese, Korean, and Vietnamese ethnicities were higher in the Multi-Ethnic category compared to their corresponding monoethnic group.
Social media is a powerful tool that can be leveraged for targeted recruitment – in this study we see how it can increase diversity amongst research participants and potentially be used as an effective tool for information dissemination. This work can be expanded in the future by looking into other social media platforms that are more targeted towards Asian populations and by disaggregating the data even further to fully understand the diversity present in the Asian population.
"Light and Sound, Not Song and Dance": Cybernetic Subjectivity in the Environmental Art of the Pulsa Group, 1966–1973
Keywords:  Program in Science
Pulsa
STS
cybernetics
art and technology
environmental art
Thesis

The proliferation of computing technologies and their attendant futurisms throughout the 1960s and 1970s prompted engineers and artists alike to reckon with a world humans would share with artificially intelligent machines. However, current scholarship around this period of techno-aesthetic experimentation lacks a full-scale exegesis of the work of the Pulsa Group, an artists collective composed of seven Yale University graduates who lived communally and created programmed environments from 1967 to 1973. This thesis makes use of archival research and interviews to chart the arc of Pulsa’s career, beginning with the light and sound environments they constructed in a New Haven loft and ending with their implementation of a feedback-enabled environment wherein human movements elicited responses from a computational infrastructure. I characterize the group’s iterative work process as moving toward evolutionary environments aimed at evolving the human perceptual panoply to better cope with a dawning cybernetic age. The audience’s experience of a Pulsa environment bolsters this project in that the boundary between art and viewer or object and subject becomes blurry—the human and the machine are in fact interdependent. Eventually, Pulsa took their environments to the urban environment, where the dream of facilitating dialogue between computers and their users became an element of city planning. Finally, Pulsa’s work evolved toward mutualistic feedback between participants and environment, where input from people in the space affected the system output. Rather than attempting to control participant behavior, I argue, Pulsa’s interactive works created a networked environment in which action could occur and be fed back into the system. In the resultant social vision, control persists not in the overt control of behavior, but in the creation of seemingly endless opportunities for action within a system that learns from those choices.
Limitations of the Intellectual Borders created by the Human Rights Field: A Fractal Exploration of Drummond in Chiriguaná, Colombia
Keywords: Center for Latin American Studies
Colombia
Land use > Environmental aspects > History
Text
Thesis

Drummond is a powerful coal mining company operating in Chiriguaná, Colombia. Based in Alabama, the corporation ranked in 2018 as 165th on Forbes’ list of America’s Largest Private Companies. The coal the company mines is barely used in Colombia – the country exports 92% of the coal it produces. In the United States human rights field, Drummond is famous for allegedly hiring the AUC paramilitary to murder three of its union leaders. In the human rights reports on Drummond, this event is detailed only within the context of Colombia’s internal armed conflict. This thesis aims to widen the lens, exploring Drummond’s presence in Chiriguaná through an intersectional approach based in border theory and environmental history. In doing so, it argues that the limited perspective of human rights reports reproduces the arbitrary borders that help create the conditions for the very abuses the field denounces. The thesis concludes by imagining alternative practices for the human rights field that are based in connectedness rather than separation.
Linking Processing Speed And White Matter: a bridge between Education and Neuroscience research
Keywords: Processing Speed
White Matter
Educational Neuroscience
Stanford
School of Humanities and Sciences
Symbolic Systems
Thesis

In the first chapter of this thesis, I review the history of processing speed as a cognitive capacity since the late 19th century. In the second chapter of this thesis, I analyze the definitional and conceptual constraints surrounding the use of ‘processing speed’ in the behavioral psychology literature. Specifically, I evaluate the degree of diversity observed in operationalized definitions of processing speed advanced in recent literature, and then present three ways to reduce this diversity in order to unify scholarly conceptualizations of processing speed in the future. In the third chapter of this thesis, I assess a candidate for an anatomical/mechanistic grounding for characterizations of processing speed as a cognitive capacity. In the final chapter of this thesis, I summarize arguments presented in chapters two and three and discuss implications for future research, as well as the importance of the research paradigm more broadly.
Literary Embodiment: Representations of Disability in Anthony Doerr's "All the Light We Cannot See"
Keywords:  Department of English
Stanford University
Department of English
Disability Studies
Disability Representation
Disability Theory
Blindness
Anthony Doerr
All the Light We Cannot See
Contemporary Fiction
Thesis

According to disability studies theories such as ‘narrative prosthesis,’ ‘aesthetic nervousness,’ and ‘aesthetic blindness,’ disability in literature is often metaphorized, stereotyped, or typologized. Through close readings and character studies, this thesis explores how Anthony Doerr’s “All the Light We Cannot See” resists, complicates, and reverses such concepts as a novel with a disabled cast.
Loan loss measurement and bank lending
Keywords: Business.

I use both theoretical and empirical models to assess how alternative measurement approaches to banks' loan loss allowances affect lending when banks are subject to regulatory capital requirements. I find that: (1) the Current Expected Credit Loss (CECL) method increases loan loss reserves on average by 16% relative to the Incurred Credit Loss (ICL) method; (2) the difference between CECL loan loss allowances and ICL loan loss allowances is larger in economic downturns than upswings; (3) banks reduce lending on average by 3.15% (50 basis points) when switching from ICL to CECL; and (4) CECL results in less procyclical lending than ICL, specifically, the difference between lending in up- vs. downturns decreases by 0.8% (37 basis points) when moving from ICL to CECL
Local and average structural evolution of halide perovskites upon compression
Keywords: Applied Physics.

Halide perovskites have emerged over the past decade as promising materials for photovoltaic solar cells. Pressure can be a powerful parameter for tuning the structures of these materials which in turn can dramatically influence their optoelectronic properties; however, previous research has only looked at the average structural evolution of various halide perovskites upon compression. In this dissertation, I describe our work studying the local structural evolution of halide perovskites upon compression using X-ray total scattering and pair distribution function analysis. First, I explore the double halide perovskite Cs2AgBiBr6. On average, this material has a cubic crystal structure, but analysis of the pair distribution function reveals local Br distortion and Cs off-centering, which are enhanced upon compression. Second, I look at the local and average structural evolution of 3-D halide perovskites, including our use of reverse Monte Carlo simulations to gain insight into the complex structural evolution of CsPbBr3. These studies highlight the importance of considering both the local and average behavior to build a more accurate understanding of halide perovskite structures, a key building block toward designing new materials with improved performance
Locality in quantum many-body systems
Keywords: Physics.

How can we understand complex quantum many-body systems without finding exact solutions? Recent developments have shown that first principle constraints can provide satisfactory or even accurate estimates for quantum observables in interacting many-body systems. This dissertation summarizes a series of results centered on implications of locality in quantum dynamics and thermodynamics. We first discuss microscopic locality bounds on quantum transport, chaos and ground states in open and closed lattice models. Such locality bounds provide useful and rigorous information in strongly interacting systems. Then we consider the problem of emergent locality in holographic theories, with analytical and numerical examples in holographic tensor networks and matrix quantum mechanics. Emergent locality and causality are detected and analyzed, augmenting our microscopic understanding of holography
Long-time asymptotics for reaction-diffusion and stochastic Burgers equations
Keywords: Mathematics.

This dissertation consists of two parts. In the first, we study the long-time behavior of various reaction-diffusion equations. We begin by describing a complete asymptotic expansion for solutions to the classical Fisher—KPP equation in the long-time limit. We then take up a version of Fisher—KPP with nonlocal diffusion. We show that typical nonlocal equations resemble the local model at long times; however, strongly asymmetric nonlocal diffusion can disrupt this behavior. Next, we use a connection between the Fisher—KPP equation and branching Brownian motion (BBM) to study the probability that the leading two particles in BBM are unusually far apart. This is joint work with J. Berestycki, Brunet, Mytnik, Roquejoffre, and Ryzhik. Finally, in collaboration with H. Berestycki, we study steady states, propagation, and traveling waves for a much wider class of reaction-diffusion equations in half-spaces. The second part of this dissertation explores the long-time behavior of the stochastic Burgers equation; it consists of joint work with Dunlap and Ryzhik. We draw on the theory of parabolic partial differential equations to construct stationary solutions to the stochastic Burgers equation on the line. Moreover, we show that the extremal stationary solutions are parameterized by their means and arise as stable long-time limits of constant initial data
Long-time behavior of the international trade equation and average gromov hyperbolicity
Keywords: Mathematics.

In this thesis, we will describe results that hail from two very different probabilistic models. First, we will discuss an equation that models the distribution of productivity within a global economy that allows for knowledge sharing. We will show that the equation has traveling wave solutions, and that time-dependent solutions with compact initial data converge to traveling fronts at the minimal speed with a Bramson delay. In the second chapter, we will prove that probability spaces which obey an average notion of ultrametricity have a tree-like structure, a result that has applications in many spin-glass models
Looking East: Evaluating Russia's Pivot to Asia
Keywords:  Center for International Security and Cooperation
Center for International Security and Cooperation
Russia
China
pivot
Russian foreign policy
international security
Thesis

At the September 2012 Asia-Pacific Economic Cooperation Forum, Russian President Vladimir Putin launched his “Pivot to Asia”, ostensibly launching a reorientation of Russia’s foreign policy. Yet, has Russia truly pivoted to Asia? If so, why? Data on Russia’s economic and security ties with major Asian countries illustrate that Russia’s shift to Asia is real, especially towards China. Such a shift has been motivated by the Kremlin’s desire to reduce Russia’s economic reliance on Europe in light of Western sanctions as well as shared regional security interests and elite diplomacy between Putin and other heads of state. While Putin and the Kremlin have taken deliberate actions to support a pivot east, broader geopolitical and economic trends have been at least as consequential in pushing Russia east, such as Asia’s growing economic power. Far from starting in 2012 with Putin’s pronouncement, Moscow continually looking east is part of a historical pattern dating back several hundred years. As the global balance of power shifts towards Asia, U.S. policymakers must be cognizant of the second and third order effects U.S. foreign policy can have on the Kremlin’s ties with major powers in Asia.