News Media Sentiment Toward Chinese AI: a Comparative Analysis with Belt and Road Initiative Involvement and Public Opinion on China

This study evaluates different countries\u27 news media’s sentiment towards Chinese AI, between May 2023 and May 2024, by using Microsoft Azure NLP Sentiment Analysis. The results are then compared with the country’s public opinion on China and its involvement in the Belt and Road Initiative (BRI). For this study 12 countries have been selected which are USA, Australia, Pakistan, Peru, Russia, Romania, Italy, Greece, Portugal, Philippines, Brazil, and Egypt. For each one, GNews Application Programming Interface (API), which has access to more than 60,000 global news sources, was used to aggregate relevant news articles based on queried keywords. The collected set of articles related to the topic of China+AI was compared with a set of aggregated articles related to AI, which was used as the control variable. The results showed no significant patterns between a country’s involvement with BRI or public opinion of China. This is contradictory to the theory of Commercial Liberalism and provides valuable insights regarding limitations of China’s soft power

Find My Friends: Location-Sharing Ideologies and Peer Surveillance Practices

This thesis investigates the use of Find My Friends in the context of the Claremont Colleges. Students choose to location-share under initial rhetorical justifications of social reciprocity, and community-orientedness, and peer-safety. Drawing from ethnographic interviews conducted with users at the colleges, I argue that the infrastructure of Find My Friends in conjunction with the social and physical proximities of the Claremont environment creates a distinctive condition where users are subject to what I term as a “virtual, neoliberal, and participatory panopticon.” Here, users are seemingly empowered through the application’s neutralizing collapse of reciprocity and hierarchy that are seen in conventional surveillance structures. Instead, I suggest that Find My Friends disempowers its users as it reproduces the logics of surveillance on an interpersonal scale and invades the ways in which we move and interact within the social sphere

State Suspension vs. Termination of Medicaid on Recidivism Outcomes

This paper seeks to explore the relationship between Medicaid and recidivism through the lens of states suspending versus terminating Medicaid enrollment while an individual is incarcerated. Looking at post-ACA data from 2015, 2017, and 2018, and using a staggered difference-in-difference design, I find that suspension, rather than termination, reduces recidivism when interacted with Medicaid enrollment on a broad scale and among certain populations, including White non-Hispanics, individuals above 25 years old, and males. These findings suggest that policymakers should support more local operations, such as pre-release programs connecting individuals with Medicaid, in conjunction with suspending Medicaid on a statewide basis

The Plants Don\u27t Give a Fuck! : The Three Pillars of Queer Eating Disorder Recovery

This project seeks to make visible the often overlooked and invisibilized stories of trans and non-binary folks who struggle with their relationships with body and food, to begin the process of cultivating a pedagogy of programming geared towards queer youth who struggle with food into both conversations and community with farmers, and to use farming as a way of rethinking and reconceptualizing relationships with food land and labor

Fractured Simulacra: How Media Echo Chambers Shape Divergent Realities in Public Opinion

This thesis empirically investigates the relationship between exposure to time-varying partisan news content and individual policy attitudes. Combining individual-level Cooperative Election Study data (2020–2023, N≈68,000 for seven policy outcomes) with daily Fox News and MSNBC transcripts, I analyze how fluctuations in media narratives associate with public opinion. Leveraging large language models, I classify all relevant news segments by topic and ideological stance (liberal/conservative), generating daily time series of content volume and slant for each channel and policy issue. These series construct respondent-specific exposure measures based on self-reported viewership and 7-day rolling aggregates of media content preceding the survey interview date. OLS regression models predict standardized policy attitudes using interaction terms between viewership and media aggregates (Net Tone; or Volume and Slant simultaneously), controlling for demographics, ideology, party identification, and county and year fixed effects. The analysis finds a robust association between the ideological slant of recent media exposure and policy attitudes. Controlling for content volume and fixed effects, exposure to more liberal-slanted coverage in the preceding week significantly associates with holding more liberal views across nearly all policy domains (most p\u3c0.001). For instance, a one-unit increase in the normalized liberal slant (-1 to +1) of Fox News\u27 coverage of assault weapons over a week correlates with a 0.146 (SE=0.012) point increase in viewer support for a ban. This slant effect generally dominates the smaller and less consistent associations found for content volume. These findings demonstrate a strong correlation between how partisan outlets frame issues and viewer opinions, distinct from channel selection, highlighting the value of granular content analysis for understanding media\u27s role in shaping policy views

Priming Effects of Grammatical Gender on Gender Conceptualization in French

Several Indo-European languages have grammatical gender constructs in which nouns are assigned to a gendered noun class, typically masculine or feminine. Speakers of such languages must categorize inanimate nouns as masculine or feminine, despite these objects lacking biological sex. Some research has been conducted on whether grammatical gender affects the gender conceptualizations of inanimate objects: for example, do individuals perceive grammatically feminine objects as having more feminine qualities? The question of the effects of grammatical gender on cognition is rooted in the theory of linguistic relativity, first coined by Edward Sapir and Benjamin Whorf in the 1950s (Sera et al., 1994). This theory claims that cross-linguistic differences affect how speakers of different languages perceive reality. Research on linguistic relativity has explored several language constructs, including how different languages encode concepts of time, spatial orientation, color discrimination, number representations, and object categorization (Samuel et al., 2019). However, studies examining the effects of grammatical gender have yielded conflicting results, and often only focus on native speakers. This study examined the potential effects of priming with grammatical gender on conceptual gender associations in intermediate L2 French speakers. Participants were primed with images of inanimate nouns that were either grammatically masculine or feminine in French, then completed a lexical decision task in which target words represented culturally masculine or feminine activities. Results indicated little to no impact of grammatical gender on gender conceptualization. The findings of this study imply that grammatical gender may not affect gender concepts in non-fluent speakers of a gendered language, but the conflicting nature of the literature in this field calls for further research

Exploring Balanced Partitions in Triangular Lattices

This thesis investigates balanced partitions of spanning trees in triangular lattice graphs, extending previous work on grid graphs. The study of spanning tree partitions has applications in randomized algorithms and graph-based sampling techniques. First, we review foundational results on spanning trees in grid graphs, including probability bounds for obtaining balanced partitions when dividing a graph into two components. Then, we extend these methods to triangular lattices. Specifically, for a hexagonal region of a triangular lattice graph with a partition, we seek to establish a minimum probability that a randomly selected spanning tree can be divided into two balanced components. By adapting spanning tree distribution techniques, using a careful study of random walks, and employing combinatorial probability bounds, we provide theoretical guarantees for balanced partitions in triangular lattices. These results contribute to both theoretical graph analysis and practical applications in randomized algorithms and partition-based sampling methods. This research holds potential applications in redistricting electoral districts in the United States, equipping statisticians and political scientists with a framework for evaluating electoral boundary fairness

Reject Modernity, Embrace Tradition: Unpacking Gender Roles in Social Media Performances of the Good Life

What do JD Vance, tradwife influencers, and the “sprinkle sprinkle” movement have in common? They all have something to do with the increasing popularity of an apparent return to traditional gender roles. This thesis is an intersectional investigation of women’s gender roles in relation to class and race as they appear in different performances of “the good life” on social media. Through a series of personal essays, this thesis explores how these media examples represent a deeper political unhappiness with present conditions. This thesis takes the time to unpack the different sides of discourse surrounding each subject, and counters the rapid turnover of social media content which often leads to misinformation and inflammatory reactions. I unveil what specific causes for unhappiness are perhaps at work in these media examples: capitalism, white supremacy, and patriarchy. By interweaving both personal experience with rigorous analysis, this thesis traverses the boundaries of public and private, and allows readers to both feel emotional resonance and critically engage with what these expressions of gender roles reveal about our political moment

The Making of Mathematics: An Interview with Carlo Cellucci

Carlo Cellucci is professor emeritus of the Sapienza University of Rome, and has written books on logic, mathematics, and philosophy. In the following interview conducted via back-and-forth email correspondence, he discusses his 2022 book, The Making of Mathematics: Heuristic Philosophy of Mathematics [3], which presents a new paradigm for thinking about, doing, and teaching mathematics

Modeling MRSA Co-colonization in a Hospital Environment: A Stochastic Approach

Methicillin-resistant Staphylococcus aureus, (MRSA) remains a significant public health threat due to its continued prevalence in communities and hospitals across the country and its growing resistance to lactam antibiotics. This paper is concerned with modeling a hospital in which both strains of MRSA, Community Acquired MRSA and Hospital Acquired MRSA, are present as well as individuals who are co-colonized with both strains. In addition to a system of Ordinary Differential Equations, our model will utilize both a Continuous Time Markov Chain and a system of Stochastic Differential Equations to better model the emerging epidemic in the hospital. Before building these two models, we outline the theory behind Discrete Markov Chains, Continuous Time Markov Chains, and Branching Processes. We will use our model to understand how hospital hygiene and the prevalence of MRSA in the community affect how endemic MRSA becomes in the hospital. We find that both increased hospital-hygiene and lower levels of CA-MRSA in the surrounding community decreases the peak levels of the MRSA epidemic. As hospital-hygiene decreases and MRSA becomes more prevalent in the community, the MRSA epidemic becomes much more variable and harder to predict, making it more difficult to track and mitigate the epidemic