VictorJuiz/thesis huggingface dataset:
Essays on pretrial detention decision-making : evidence from Brazil
Keywords: Law.

This dissertation investigates the Brazilian pretrial criminal decision-making through a series of quantitative case studies relying on a tailor-made dataset including over 2,000 defendant-level observations from a large city (Campo Grande, Mato Grosso do Sul). In the overall, this research analyzes the Brazilian judicial practice to identify pretrial detention's key mechanisms and explanatory factors, assess its effects on case outcomes and explore the potential effectiveness of introducing statistical pretrial risk assessment in the country. The dissertation dialogues with the growing, though still U.S.-concentrated, empirical literature on pretrial justice by providing novel quantitative legal analyses from an influential Global South jurisdiction with the world's third largest incarceration population and a non-adversarial criminal procedure tradition. The first article provides an overview of pretrial detention in the first 100 days with descriptive statistics and inferential analyses that tease out the main case and defendant factors associated with pretrial decisions. The second article compares the real performance of judges in assessing defendant risk of failure to appear (FTA) with a simulated scenario where they rely on statistical risk prediction to decide between pretrial detention or release. Finally, the third article investigates the causal inference question of whether and the extent to which pretrial detention affects case outcomes
Essays on the politics of scientific and technological change
Keywords: Humanities and Sciences.
Political Science.

This dissertation brings together three papers that explore the relationship between politics and scientific and technological change, paying close attention to how political actors respond to changes in science and technology. The first two papers see technology as exogenous to politics, and study the political consequences of different methods of adjustment to new production technology. The first paper tests and finds evidence against a common conventional wisdom -- that reemploying the losers from technological change will reduce their political grievances and mobilization. The second paper shows that institutions designed to deal with one type of job loss -- that due to trade competition -- might direct collective action by the losers from another type of job loss: automation. The last paper takes a step back and asks whether scientific knowledge -- in this case, knowledge about environmental harm -- is truly exogenous to the interests of powerful actors. I show that powerful states have an incentive to alter scientific information from international institutions in an effort to secure a more favorable climate agreement
Estimation and testing methods for causal inference with interference
Keywords: Humanities and Sciences.
Statistics.

Causal inference is one of the core areas of research in modern data science that allows researchers to determine whether a specific intervention or treatment has an effect on an outcome. In its most basic form, causal inference is concerned with understanding the "cause and effect" relationship between variables. This requires going beyond correlation to understand whether changing one variable leads to a change in another. The gold standard for inferring causality is the randomized controlled trial, which randomly assigns subjects to a treatment or control group and compares outcomes. While randomized controlled trials provide us with data to do causal inference, the subsequent statistical analysis often relies on a key assumption known as the Stable Unit Treatment Value Assumption (SUTVA). This assumption states that the treatment of one unit (or individual) does not affect the outcome of another unit. However, in many real-world situations, this assumption does not hold, leading to what is called interference or a violation of SUTVA. Interference can occur in various contexts such as social networks, where the treatment of one person can influence the outcomes of others, or in marketplace, where treatment of one entity can impact other entities of same type. Understanding and handling interference is a critical and complex aspect of causal inference, and it necessitates more advanced methods to correctly estimate causal effects. This dissertation offers new methodologies and theoretical results to address key issues in causal inference with interference. Specifically, we develop inferential results for causal effect estimators in panel experiments under interference, introduce novel estimation methods for causal effects with network experiments and tackle the problem of detecting interference in online controlled experiments with increasing allocation
Ethereal romanticism : dynamic materiality in German thought in the late eighteenth and early nineteenth centuries
Keywords: Humanities and Sciences.
German Studies.

This dissertation investigates how new scientific developments around the concept of "aether" changed the way German Romantic writers conceived of humans' interactions with nature and how literature and poetic forms are transformed through such changes. From Greek mythology and presocratic theories of nature through Newton's hypothetical space-filling medium to the nineteenth-century electromagnetic and field theories and the emergence of wireless technologies in the twentieth century, aether was one of the most indispensable yet elusive concepts in the history of science. Literary and cultural scholars have usually considered the occult aspects of the term as being most relevant to literary and intellectual history. This dissertation argues instead that Schelling, Hölderlin, Novalis, and Jean Paul Richter use ancient and contemporaneous theories of the fluid, chemical, magnetic, and vibratory interactions of aether to develop materialist conceptions of the human mind and poetry as well as proto-ecological modes of writing. In their scientific and literary thought experiments that center around aether, these writers appeal to nonhuman models, including mythological figures associated with waves of all sorts (light, water, and sound), animals such as the South American electric eel that can discharge electricity in water, and instruments such as the Aeolian harp, which is played by the wind. These experimental poetics with temporary and fluid forms, in turn, help Romantic writers develop dynamic and performative conceptions of matter and non-anthropocentric understandings of the relationship between humans and their environment. This project contributes to the growing scholarship on the relationship between literature and science in German Romanticism and engages in a productive dialogue with contemporary new materialist theories and ecocriticism.
Ethnic identity and homeland politics in the Oromo diaspora
Keywords: Humanities and Sciences.
Sociology.

In this dissertation, I address the mismatch between how scholars employ ethnoracial categories in studies of race, ethnicity, and immigration and how individuals make sense of their identity on the ground, in their day-to-day lives. Using the case of Oromo immigrants from Ethiopia, I show how scholarship on immigration and identity can be improved by attending to subnational ethnic diversity, which allows for greater analytical clarity by teasing apart the distinctions between race, ethnicity, and nation and their relationship to one another. In undertaking this effort, I show how a shift in our level of analysis can make visible a deeper, more nuanced understanding of race/ethnicity and its import in social cohesion, conflict, and immigrant integration. This dissertation highlights the importance of attending to subnational ethnic diversity in two important ways. First, I show how the conventional use of Ethiopia(n) as a category of analysis does not align with my respondents' lived experience of Oromo as a category of practice. When studied as Oromo immigrants rather than Ethiopian immigrants, my respondents show how Blackness as an identity and lived experience transcends the U.S. context to include understandings of Blackness also situated in the homeland context via a shared experience of minority subjugation. Second, my treatment of Oromo immigrants as a unique subset of Ethiopian immigrants demonstrates how notions of indigeneity are as central to the formation and salience of Oromo identity as are notions of Blackness. That Blackness and indigeneity are more intimately linked than scholars have often understood them to be opens the door for a more serious engagement with Black indigeneity as a topic of inquiry.
EVALUATING MODELS OF REFERRING EXPRESSION PRODUCTION WITH CROSS-LINGUISTIC DATA
Keywords: referring expression production
rational speech act
village sign language
Text
Thesis

Redundant modification in referring expression production varies both within language (e.g., English speakers produce more redundant color than size modifiers) and cross-linguistically (e.g., English speakers produce more redundant color modifiers than Spanish speakers). It is an open question whether these asymmetries are the result of asymmetries in the general referential utility of color and size modifiers or of incremental language processing pressures. Cross-linguistic investigations of redundant modification are important to this debate: similar cross-linguistic rates of redundant modification would suggest a strong role for general referential utility. In contrast, lower prevalence of redundant modification in languages with post-nominal modification suggests a strong role for incrementality. Here, we test whether differences in redundant modifier use are systematic for a particularly interesting language: Central Taurus Sign Language. As a language in its infancy, CTSL has no established conventions, and therefore provides us with a unique opportunity to explore how redundancy emerges in the initial stages of language formation. We also ask whether redundant modification patterns replicate in Turkish and we compare our results to English. Using data from these three languages, we evaluate computational models of referring expression production that each make different assumptions regarding the source of asymmetries in the production of redundant modifiers. The data suggest a limited role for incrementality, and support accounts of redundancy that center the role of referential utility. However, this conclusion is limited by data concerns.
Evaluating Race-Related Lived Experiences in BIPOC Youth Participating in a Telehealth Intensive Outpatient Program
Keywords: BIPOC
Mental health
Community mental health services
Stigma (Social psychology)
Racial Discrimination
Belongingness
Racial trauma
Young adults
Adolescents
Text
Thesis

Background. Youth mental health is a significant issue in the United States; especially for young adults and adolescents who identify as Black, Indigenous, or people of color (BIPOC). BIPOC youth traditionally face greater barriers to care, such as lower insurance coverage and provider bias, and historically have suffered poorer health outcomes compared to their non-BIPOC counterparts. To understand how to most effectively help BIPOC youth with mental health issues, more data is needed. However, research on BIPOC mental health and mental healthcare programming is lacking. This study aims to better understand the needs and race-related lived experiences of BIPOC youth in a virtual intensive outpatient setting in order to improve programming curriculum and better meet the specific needs of BIPOC patients.
Methods. A survey with four measures–general belongingness, racial trauma, race-related discrimination, and internalized mental health stigma–was administered to 24 individuals in Charlie Health’s (a company offering virtual intensive outpatient programming for youth) young adult and adolescent BIPOC support groups. Data collected in this survey was compared against results in the general population, obtained from the literature.
Results. The findings suggest that BIPOC youth participating in IOP support groups report significantly lower levels of belongingness, and higher levels of racial trauma and race-related discrimination relative to their peers in other contexts, as seen in the literature. Results from the internalized stigma of mental illness measure were nonsignificant.
Conclusions. Research that improves understanding of BIPOC patient race-related experiences is important to enhance the quality of care provided to them. BIPOC youth in intensive mental healthcare treatment settings like Charlie Health could benefit from programming specific to their race-related lived experiences. Based on the results of this study, BIPOC programming curriculum could be more effective with the augmentation of certain topics, like belongingness in society and race-related discrimination, as well as a greater focus on unpacking racial trauma. Incorporating elements from Charlie Health’s BIPOC program–such as cultural competency training in clinicians–would also be beneficial. Further research on mental health stigma and outcomes in this population is necessary in order to make definitive curricular
recommendations.
Evolutionary dynamics of conformity
Keywords: Humanities and Sciences.
Biology.

Conformist and anti-conformist cultural transmission biases have been documented in several species, in contexts from mating to finding food, and have been studied theoretically, with mathematical models. Many previous models have included a set of simplifying assumptions: (1) individuals observe a small number of cultural 'role models, ' n, and acquire a cultural variant from this sample with a single (anti-)conformity coefficient, D; (2) both n and D are constant over time; and (3) there are two cultural variants in the population (for example, the 'presence/absence' of a behavior). In Chapters 2-4, I vary each of these assumptions in turn, aiming to contribute to bridging the gap between theory and its applications to real-world scenarios. In Chapter 2, offspring can observe any number n of role models and apply different conformity rules to different configurations of sampled role models. A wide array of population dynamics emerge that were not possible in the canonical conformity model, including novel equilibria, stable cycles in variant frequencies, and chaos. In Chapter 3, n and the conformity coefficients can vary stochastically over time. This study reveals a variety of differences between deterministic and stochastic conformity models, but also proves that if conformity is expected on average in the stochastic model, the population converges to one of the three equilibria seen in the deterministic conformity model. Chapter 4 incorporates more than two cultural variants into the deterministic conformity model and uncovers novel types of polymorphic equilibria, variant frequency cycles, and chaos. Overall, Chapters 2-4 show that altering the assumptions of the standard conformity model may produce a more realistic representation of the wide range of properties that can emerge under (anti-)conformity. Chapters 5 and 6 explore how (anti-)conformity, in conjunction with other cultural transmission biases and/or genetic transmission, may affect the evolution of two phenomena—altruism and cumulative culture—that have puzzled evolutionary theorists. An altruistic behavior paradoxically reduces one's own fitness to increase that of another, and has commonly been modeled as a genetically transmitted trait. Chapter 5 shows how cultural transmission of altruism, including conformity, anti-conformity, and a "content" bias for altruistic behavior, changes the conditions under which this behavior evolves compared to those under purely genetic transmission. Chapter 6 seeks to explain why cumulative culture, i.e., the incremental improvement of a cultural trait, such as a tool, over time, is seen in few non-human animals despite its potential advantages. Results show that small population sizes and conformist transmission can hinder cultural accumulation
Expanding the capabilities of biosensors with novel molecular switches
Keywords: Engineering.
Electrical Engineering.

Biosensors capable of tracking the body's molecular state have tremendous potential to improve lives by making healthcare more accessible, personalized, and preventative. At the same time, developing biosensors that are both compatible with point-of-care or continuous monitoring and can accurately track a wide range of clinically important biomarkers poses a tremendous technical challenge. These sensors must operate without the sample processing employed by conventional laboratory diagnostic assays and must measure targets rapidly with molecular sensitivity and specificity within complex biofluid samples. These demands may be met by biosensors based on "molecular switches" -- engineered receptors that bind molecular targets with high specificity and undergo a binding-induced conformational change that produces measurable optical or electronic signals. However, to date these molecular switch biosensors have remained limited to sensing only a handful of molecules. It remains an outstanding challenge to develop generalizable strategies to methods for engineering molecular switches to sense the complete range of health biomarkers. In this dissertation, I begin by considering how we can develop sensors that are compatible with real world, day-to-day use. I analyze the diagnostic value of biosensing in dermal interstitial fluid, a biofluid with emerging interest for use with minimally invasive and continuous wearable sensors. The remainder of the dissertation focuses on three projects where I expand the generalizability molecular switches, enabling more rapid development of biosensors for new biomarker targets. In the first project, I introduce an approach for engineering off-the-shelf antibodies into antibody-based molecular switches that achieve continuous optical biosensing by augmenting them with a rationally designed DNA-linked competitor molecule. In the second project, I develop a universal protein-based competitor molecule that provides an even more universal method for our antibody-based molecular switch design to be applied to sensing new targets. In the third project, I develop a rational design approach for engineering DNA-based molecular switches that have pH-dependent properties which can be tailored to improve biosensor performance, and for potential drug delivery applications. Taken together, these advances in molecular switch design offer a toolkit of generalizable strategies that can be used to develop next-generation biosensors which sense a wide range of biomarkers for addressing a wide range of clinical needs
Expanding the Horizons of Synthesizable Materials: A Study of Various Machine Learning Techniques on Materials Synthesizability Prediction
Keywords: Program in Engineering Physics
Machine learning
computational material science
Text
Thesis

This study aims to provide insights into better ways of applying machine learning (ML) to predict and discover new materials. Specifically, this research focuses on comparing the performance of different ML techniques that are trained with data from the Materials Project Database and the Inorganic Crystal Structure Database to identify effective ML techniques that can perform materials synthesizability prediction. Machine learning (ML) is a subfield of artificial intelligence that allows computers to learn and improve from data without being explicitly programmed. By using ML, researchers can analyze and interpret large amounts of data related to materials' properties, structure, and performance. This can lead to the discovery of new materials with desirable properties, as well as the optimization of materials synthesis and processing. In this study of synthesizability, we report results on a number of different models for predicting synthesizability under different data imbalance scenarios. By defining the 100% precision-recall curve area be the best performance a perfect ideal model can achieve, our best performance model is a Multi-Layer Perceptron (MLP) model that exhibits a hold-out set precision-recall curve area of 99% when the dataset is balanced. Our results also show that the MLP model is the most resistant to the influence of data imbalance with a hold-out set precision-recall curve area of 98% when the imbalanced dataset has an unlabeled-to-labeled ratio of 4:1 and a hold-out set precision-recall curve area of 90% when the imbalanced dataset has an unlabeled-to-labeled ratio of 16:1.
Expansion microscopy and other tools for investigating the cell-material interface
Keywords: Humanities and Sciences.
Chemistry.

Surface topography on the scale of tens of nanometers to several micrometers substantially affects cell adhesion, migration, and differentiation. Recent studies using electron microscopy and super-resolution microscopy provide insight into how cells interact with surface nanotopography; however, the complex sample preparation and expensive imaging equipment required for these methods makes them not easily accessible. Expansion microscopy (ExM) is an affordable approach to image beyond the diffraction limit, but ExM cannot be readily applied to image the cell-material interface as most materials do not expand. Here, we develop a protocol that allows the use of ExM to resolve the cell-material interface with high resolution. We apply the technique to image the interface between U2OS cells and nanostructured substrates as well as the interface between primary osteoblasts with titanium dental implants. The high spatial resolution enabled by ExM reveals that although two proteins, such as AP2 and F-actin, both accumulate at curved membranes induced by vertical nanostructures, they are spatially segregated. We also employ upconversion nanoparticles as a better fluorophore to visualize proteins of interest in ExM. We believe that our protocol will enable the use of ExM as a powerful tool for cell-material interface studies. Additionally, we explore extracellular matrix fiber synthesis and proteomics as further tools to investigate the cell-material interface.
Experimental methods in economics : three applications
Keywords: Humanities and Sciences.
Economics.

This dissertation comprises three papers employing a diverse set of experimental methods to examine behavioral aspects of individual decision-making across distinct domains: charitable giving, misinformation on social media, and considerations surrounding others' autonomy of choice. Chapter 1 presents two experiments conducted on PayPal's Give at Checkout microgiving feature to learn about the effect of 1) information about charity outcomes on donations, and 2) exposure to these point-of-sale micro-giving requests on subsequent giving. Chapter 2 evaluates three distinct versions of a low-cost and scalable five-day text message educational course on drivers of misinformation sharing by conducting a field experiment with approximately 9,000 participants. Chapter 3 experimentally investigates the objective function of third parties who can impose binding minimum contribution requirements on a group of ten players playing a linear Public Goods Game.