UC Irvine

Digital markets are built on data, low-friction access, and user trust. This dissertation studies what happens when each of these pillars is disrupted. Across three essays, it shows that privacy regulation, registration-based access barriers, and public revelations of workplace misconduct can materially alter consumer purchasing, attention allocation, and platform choice. The first essay examines the unintended consequences of the California Consumer Privacy Act (CCPA) for consumer commerce. Using the CCPA as a natural experiment and combining billions of payment transactions with browsing data and firm-level measures of advertising technologies, the essay shows that Californians purchased less, returned more, and spent more time browsing after the law took effect. Firms subject to the regulation also reduced their use of ad-related technologies. These findings suggest that stronger privacy protections may unintentionally weaken personalization and product-consumer matching, reducing commercial activity even as they expand consumers' control over personal data. The second essay studies the New York Times' introduction of a registration wall as a first-party data collection strategy. Using web browsing data together with a regional measure of privacy salience based on cumulative exposure to data breaches, the essay finds that registration walls generate heterogeneous responses across user segments. News-singlehomers reduce engagement after the wall is introduced, whereas news-multihomers slightly increase engagement. Higher privacy salience attenuates the decline among singlehomers and strengthens the positive response among multihomers. When users disengage, their attention shifts primarily toward search engines and video-sharing platforms, revealing broader ecosystem consequences of registration-based access barriers for news consumption. The third essay investigates how public whistleblowing about workplace sexual harassment and discrimination affects consumer demand in platform competition. Exploiting a blog post by a former Uber employee describing sexual harassment, discrimination, and the company’s response—an account that quickly went viral on social media—as an exogenous reputational shock, the essay shows that Uber usage declines while Lyft usage rises among riders most able to switch between the two platforms. These effects are strongest in markets with greater local attention to the event and among riders predicted to be female, highlighting how misconduct toward minorities can translate into meaningful demand-side consequences in consumer markets. Taken together, the three essays demonstrate that consumer behavior in digital markets is shaped not only by prices and product attributes, but also by data governance, access design, and corporate legitimacy. The dissertation contributes to research on privacy regulation, digital media monetization, and platform competition, while offering practical implications for firms and policymakers seeking to balance personalization, access, and accountability in the digital economy.

The distributed training of machine learning models via gradient descent is generally conducted by iteratively computing the local gradients of a loss function and aggregating them across all processors. Communicating these gradients during aggregation is often a major cost but sparsification techniques can greatly improve efficiency. One such technique, Top-k gradient compression, ensures that only the k largest components of each local gradient are sent. However, effectively scaling this method can be challenging. The standard ring AllReduce algorithm, which is frequently used to aggregate dense gradients, lacks a counterpart that is optimized for sparse data. Notably, ring algorithms are contention-free, which generally make them easier to scale than other collective communication algorithms. Thus, in practice, the ring AllGather algorithm, which can be trivially adapted for sparse data, may be used instead, even though its bandwidth costs are proportional to the number of utilized processors (unlike ring AllReduce). To provide a more scalable contention-free alternative, we present a variant of ring AllReduce that has been better optimized for sparse data. We compare it to the standard dense ring AllReduce and ring AllGather algorithms, and we evaluate it empirically using gradients sampled from fine-tuning Llama 2 7b.

English academic writing is a critical yet challenging skill for learners in English as a Foreign Language (EFL) contexts. The rapid integration of digital tools, accelerated by the COVID-19 pandemic, has transformed writing instruction; however, evidence of its pedagogical effectiveness remains fragmented and often overlooks teacher perceptions and genre-specific impacts. This three-study dissertation addresses these gaps by investigating the role of digital tools in EFL writing instruction within the EFL higher education context, employing a multi-method approach to triangulate evidence from student outcomes, meta-analytic synthesis, and teacher experiences.Study 1 conducted a classroom experiment with 111 Chinese undergraduates, comparing infographic-based pre-writing to traditional outlining. Results showed that infographic creation significantly improved summary-writing quality, source use, and self-efficacy, but not opinion writing, highlighting the genre-sensitive nature of tool effectiveness.Study 2 synthesized 17 experimental and quasi-experimental studies (N = 1,085) through a meta-analysis. It found a statistically significant, moderate overall effect favoring web-based collaborative writing (WBCW) over non-technological collaboration on writing quality (Hedges’ *g* = 0.51). Moderator analyses indicated that training was a significant factor enhancing outcomes.Study 3 explored the perceptions of seven Chinese university writing instructors through qualitative interviews. Grounded in the TPACK framework, the findings revealed that while digital tools are deeply embedded in instruction, their use is shaped by teachers' knowledge, institutional support, and access. Teachers exhibited cautious and limited integration of emerging Generative Artificial Intelligence (GenAI) tools due to concerns over academic integrity and a lack of institutional guidance.Collectively, the findings demonstrate that technology enhances EFL academic writing most effectively when tools are aligned with genre demands, collaboration is scaffolded by design and training, and implementation is supported by teacher knowledge and institutional context. The dissertation concludes by advocating for a situated, tool-genre-task alignment perspective in future research and practice, moving beyond technocentric adoption to support equitable and effective writing instruction in diverse EFL settings.

Self-renewing hematopoietic stem cells (HSCs) produce billions of blood cells a day to maintain peripheral blood and immune cells in circulation. Inflammation can alter the balance of steady-state hematopoiesis, and disrupted hematopoiesis can lead to blood disorders or cancers. Over a lifetime of cell divisions, HSCs may acquire somatic mutations that provide a competitive advantage over their wild-type counterparts. The clonal expansion of a mutant HSC population is termed “clonal hematopoiesis” (CH). CH is linked to an increased overall risk of mortality due to incidences of cardiovascular disease and transformation into hematological malignancy. Tobacco and nicotine use remain the leading preventable drivers of cancer risk, and both direct and secondhand exposure to combustible cigarettes or electronic nicotine devices perturbs immune function and hematopoiesis. The World Health Organization estimates more than 100 million people across the world are using electronic cigarettes, or e-cigarettes, but the health impacts of these “safer” e-cigarette alternative have yet to be fully elucidated. E-cigarettes have been associated with inflammation and oxidative stress, which can provide selective pressures for the outgrowth of CHIP mutant cells.Here, we evaluate the impact of e-cigarette vapor and combustible cigarette smoke on in vitro cell inflammatory responses and in vivo long-term hematopoietic differentiation. The overarching goal of this project was to understand further how an inflammatory lifestyle stressor, such as smoking, contributes to aberrant hematopoiesis in wild-type normal stem cells, Tet2- deficient cells, and JAK2V617F mutant cells. In cell-based studies, cigarette smoke extract (CSE) and e-cigarette vapor extract (EVE) consistently suppress LPS-induced TNF-α secretion across macrophage/monocyte models, including primary mouse and human cells and complementary cell lines, indicating a reproducible immunosuppressive effect on mature myeloid cells. To assess consequences of smoking behavior in vivo, we used a custom nose-cone inhalation system to deliver controlled exposures to combustible cigarette smoke or e-cigarette aerosol to mice. Chronic exposure increased myeloid proliferation, a hallmark of HSC aging. Taken together, these results support a model in which tobacco exposures blunt innate immune responsiveness while simultaneously driving myeloid expansion conditions that accelerate hematopoietic aging and promote the expansion of mutant hematopoietic cells.

One-dimensional (1D) and quasi-1D (q-1D) van der Waals (vdW) materials, which have strong bonding along only one crystallographic axis, have emerged as powerful class of solids that hosts novel electronic, optical, and quantum properties useful for next-generation electronics. These materials can, in theory, be thinned to the angstrom scale due to the ideal vdW surfaces along two axes. In practice, achieving atomically precise single chains of these materials poses a significant challenge, as conventional top-down exfoliation and bottom-up growth techniques consistently retain interchain bonding, especially in q-1D materials with anisotropic interchain bonding motifs. The question then arises: Is there a synthetic approach that would enable the suppression of all inter-chain interactions, leaving only intra-chain covalent bonding in one dimension? Using the model q-1D pnictogen chalcogenides (Pn2Ch3; Pn = Sb, Bi; Ch = S, Se, Te), chosen for the highly anisotropic structural complexity and strong inter-chain bonding combined with distinct photophysical properties, we explore encapsulation within ultranarrow nanotube growth templates to precisely define the growth of the material in sub-nanometer length scales. The deployment of these nanotube templates as encapsulants overcomes the inter-chain interactions in these phases to isolate single q-1D chains by affording physical space that directly matches the size of a single chain. More importantly, we can also probe many chains simultaneously in a collective using conventional spectroscopic techniques used in ensemble samples, allowing us to access nanoscale properties through bulk measurements. Herein, not only do we gain insight into structural and electronic properties of these single chains, but we also further our understanding of anisotropic bonding in the bulk structure by understanding how it affects single chain accessibility. As technological devices advance through shrinking and densification, understanding material properties at the atomic limit becomes increasingly vital. Our results demonstrate a powerful tool for synthesizing and studying precisely defined single inorganic chains that approach the atomic limit.

Rates of food insecurity in the military, which are higher than those in comparable communities, remain an ongoing issue. Adolescents with military parents may also struggle to cope with frequent moves and parental deployments. Using a state-wide database that included children of military personnel, we measured the association between skipping breakfast on the day of the survey and mental health screening data scores. Over 43% of students in our sample reported skipping breakfast. These students reported higher mean, median, and 90th percentile stress level scores (μ = 10.9, M50 = 10, M90=19) than the students who did not skip breakfast (μ = 9.4, M50 = 8, M90=16). Groups with increased levels of high distress (>90th percentile) included students who skipped breakfast (17.3%), females (14.4%), gender minorities (36.3%), American Indian/Alaska Native (16.0%), and Hispanic/LatinX students (13.1%). Logistic regression showed that skipping breakfast increased a student’s odds of developing stress by 2.1 (OR 2.1). These findings demonstrate an association between skipping breakfast and mental stress in an adolescent population at increased risk for both.

In this dissertation, I investigate how identity, attitudes, and social context shape adolescents’ experiences of teen dating violence (TDV). Although TDV is a persistent public health concern, much of the existing literature relies on broad demographic categories and risk-based frameworks that obscure variation within adolescent populations. Drawing on survey data from the Teen Dating Experiences Survey, I examine how sexual and gender identities structure experiences of dating violence, how adolescents evaluate the acceptability of violence in romantic relationships, and where violence occurs within adolescents’ social worlds. Together, these studies advance a more nuanced understanding of TDV by centering heterogeneity in adolescents’ identities, perceptions, and relationship contexts.In Chapter 2, I examine variation in physical, psychological, sexual, and cyber TDV victimization and perpetration across inclusive sexual and gender identity categories. Contrary to assumptions that sexual and gender minority youth face uniformly elevated risk, I find substantial variation across identities. Heterosexual and cisgender youth report significantly higher rates of violence than many sexual and gender minority groups, while pansexual and asexual youth report the lowest rates across several forms of TDV. These findings highlight the importance of disaggregating sexual and gender identities when studying adolescent relationships. In Chapter 3, I investigate adolescents’ attitudes toward TDV by examining conditional tolerance of physical, psychological, cyber, and sexual violence. Results indicate that sexual identity is a strong predictor of normative evaluations of dating violence, with most sexual minority youth demonstrating lower levels of conditional tolerance than their heterosexual peers. Gender identity, by contrast, plays a comparatively limited role in shaping attitudes toward TDV. In Chapter 4, I shift attention to the social geography of TDV by examining where violence occurs and how location relates to relationship characteristics and power dynamics. I find that violence is concentrated in private settings, particularly adolescents’ and partners’ homes, while violence occurring across multiple contexts is most strongly associated with relationship power imbalances, severity, and frequency rather than demographic characteristics. Together, these findings challenge assumptions of homogeneity in adolescent dating relationships and demonstrate that experiences of TDV are structured by identity, relational dynamics, and situational context. By examining who experiences violence, how adolescents evaluate it, and where it occurs, this dissertation advances scholarship on adolescent relationships and provides a foundation for more nuanced prevention, intervention, and educational efforts aimed at reducing TDV.

This thesis is dedicated to studying the quantitative regularity of measures produced by actions of random dynamical systems and to applying these geometric estimates to products of random matrices. First, we consider smooth random dynamical systems defined by a distribution with a finite moment of the norm of the differential, and prove that under suitable non-degeneracy conditions any stationary measure must be Hölder continuous. This result is a vast generalization of the classical statement on Hölder continuity of stationary measures of random walks on linear groups. Second, we extend this framework to rougher settings by considering Lipschitz and Hölder continuous random dynamical systems defined by a distribution with a finite logarithmic moment, proving that under suitable non-degeneracy conditions every stationary measure must be log-Hölder continuous. Finally, we leverage these regularization properties to prove a Central Limit Theorem for non-stationary random products of SL(2, R) matrices, generalizing the classical results by Benoist and Quint that was obtained in the case of iid random matrix products.The content of this thesis is based on three papers, two of which ([24, 23]) are joint work with Anton Gorodetski and Victor Kleptsyn, and the last of which ([34]) was prepared with their continuous support and advice.

Flow Matching has limited ability in achieving one-step generation due to its reliance on learned curved trajectories. Previous studies have attempted to address this limitation by either modifying the coupling distribution to prevent interpolant intersections or introducing consistency and mean-velocity modeling to promote straight trajectory learning. However, these approaches often suffer from discrete approximation errors, training instability, and convergence difficulties. To tackle these issues, in the present work, we propose Straight Variational Flow Matching (S-VFM), which integrates a variational latent code representing the ``generation overview'' into the Flow Matching framework. S-VFM explicitly enforces trajectory straightness, ideally producing linear generation paths. The proposed method achieves competitive performance across three challenge benchmarks and demonstrates advantages in both training and inference efficiency compared with existing methods.

One of the oldest and most recalcitrant questions in philosophy is whether free will and moral responsibility could exist in a deterministic universe. In recent years, empirical work has revealed that people’s intuitions about this question show a robust, yet puzzling, pattern. In this dissertation, I explain the pattern of intuitions human beings have about compatibilism and argue that this pattern reveals deep features of our representational architecture. My dissertation shows why we have the intuitions about compatibilism we do, how our species came to be so cognitively configured, and why philosophers want to (but cannot) argue their way out of the intuitions furnished by our representational structures.