Boston University Theses & Dissertations

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This is the master collection of contemporary BU theses and dissertations. We plan to consolidate school- and college-specific collections into this one, and add school- and college-specific metadata to enable users to browse appropriately.

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Music of creation: exploring novel harmonic organization in choral music of the 21st century
(2025) Gracy, Thomas; Kopp, David
A novel harmonic language has emerged within certain choral works of the 21st century that is symptomatic of a more post-structuralist interpretation of musical form and tonal direction. Works by Composers Ola Gjeilo and Frank Ticheli have been canonized in repertoires of professional and amateur choirs alike, sought after for their unique color and impactful performances. Compositions of this style are common in their aim to project topics such as peace, transcendence, and metamorphosis, but are unique to the choral genre in its structural manifestation of such. These works have, in their most characteristic parts, moved beyond the conventional teleological organization of tonal harmonies, and towards a phenomenological process that, while remaining largely triadic, ambiguates function and turns attention towards the moment and away from any harmonic end goal. A unique harmonic and syntactic organization is observed in which clear direction and thematic statements are most actualized within the center of the work, surrounded by sections of an ambient, teleologically indeterminate nature, thus inverting the traditional paradigm of stability within a tonal work. As the compositions become less harmonically ambiguous and more directed, these composers create and utilize dominant and subdominant functional implications to set up tonal expectations, then subvert these implications through unexpected means. Consequently, middleground structures evolve phenomenologically, leading the listener to shift their attention away from the functional and teleological aspects of harmony, and toward entraining solely to the euphony of the music. Important attributes of the style include the mixture of smooth voice-leading progressions with classically tonal phrase structures, a seemingly wandering sense of tonal centricity projected through overall downward contour, and the prioritization of subdominant cadences.
Coffee, air fryer, and pepper for two percussionists, viola, cello and actress
(2025) Li, Chujun; Cornell, Richard
Coffee, Air Fryer, and Pepper is a multi-sensory piece that incorporates the smell of spices, the sound of preparing the spices, and music. Embracing the musicality in our daily life sounds, I found my compositions are most natural and sincere when I use meaningful sounds that happen around me as the model and the inspiration. I believe such compositions help transform one’s sound experience in daily life into a musical one. In my past pieces I have used daily conversation as sound model and apply the harmony that is naturally embedded in the speech. For example, in the piece “人有一天”, I used the sound of my grandmother’s monologue as the model, and assigned the harmony analyzed from the speech to solo Zheng and tape. Including the performance of grinding coffee beans, brewing coffee and roasting spice, Coffee, Air Fryer, and Pepper builds a bridge between the music and the audience through common everyday life experience.
Maternal enrollment in Medicaid and access to doula care: a mixed-method assessment
(2025) Safon, Cara Brooks; Clark, Jack A.
Medicaid is the primary payer for almost half of all US births. Medicaid enrollment can enable access to timely prenatal care. Yet only 68% of Medicaid-covered pregnant people attend prenatal visits during the first trimester. Late receipt of prenatal care may in part be driven by delayed Medicaid enrollment. Understanding timing of Medicaid enrollment may illuminate a path to increasing equity in accessing timely prenatal care. Enhancements to prenatal care can improve maternal health outcomes. Timely Medicaid enrollment may help enable access to such enhancements, including Medicaid-financed benefits that support maternal health. Perinatal doula care can help reduce cesarean delivery and preterm birth rates, and reduce racial inequities among PPP. This has prompted growing interest by Medicaid to support doula services. The goal of this dissertation is to improve our understanding of Medicaid as a policy lever to improve maternal health. I seek to achieve this by characterizing 1) timeliness of Medicaid enrollment prior to and during pregnancy, as well as at delivery hospitalization; (2) the research landscape on doula care policies in Medicaid programs; and (3) the policymaking process related to Medicaid support of doula care services. This dissertation includes three studies. In the first, An Assessment of Medicaid Enrollment Timing Among Medicaid-Covered Deliveries, I use the Transformed Medicaid Statistical Information System — a national database of Medicaid claims — to measure timing of Medicaid enrollment among Medicaid-covered deliveries, and associations between sociodemographic characteristics and timing of enrollment. In the second, Medicaid Reimbursement for Doula Care: Policy Considerations from a Scoping Review, I distill key policy considerations related to the inclusion of doula care as a Medicaid-covered benefit. In the third, Access to Perinatal Doula Services in Medicaid: A Case Analysis of 2 States, I conducted semi-structured interviews with key policy informants to explore facilitators and barriers to Medicaid reimbursement of doula care in Oregon and Massachusetts. Given the value of maternal Medicaid coverage and the significance of doula care, there is an urgent need to better understand patterns of Medicaid enrollment and the evolution of state Medicaid policies on doula care.
Funding the U.S. healthcare safety net: implications and opportunities of the 340B drug pricing program
(2025) Levengood, Timothy William; Cole Brahim, Megan B
This dissertation examines the role of the 340B Drug Pricing Program in the US health care safety-net and its implications for access, affordability, and health equity. The 340B Program allows certain hospitals and public health clinics that serve a disproportionate share of low-income patients to purchase outpatient drugs from manufacturers at steep (estimated 25–75%) discounts; however, the 340B statute does not specify whether discounts are to be passed along to patients nor how profits generated from full price drug sales of discount-acquired drugs (i.e., “spread pricing”) is to be spent. This has led to calls for reform. At the same time, the 340B Program is well-situated to play an important role in the delivery of care for syndemic conditions (i.e., HIV, substance use disorder (SUD), mental health disorders), which disproportionately affect marginalized patient populations.Revenues generated from the 340B program present a key opportunity for hospitals to invest in low-profit services that may especially benefit socially and economically marginalized patient populations, such as HIV and SUD services (i.e., “mission motivated” behavior). However, providers face competing financial incentives to reinvest 340B revenue into high-profit services or services with high-cost drugs to maximize spread pricing (i.e., “margin motivated” behavior). The impact of the 340B program on low-profit or syndemic service provision is unclear. The overarching goal of this dissertation is to assess the relevance of the 340B Program to hospital finances, safety-net spending, and provision of low-profit services. This dissertation has three aims. First, I synthesize what is known about the 340B Program in the peer-reviewed, empirical literature via a systematic scoping review, categorizing outcomes indicating margin- versus mission-motivated behavior by 340B providers. Second, I assess the financial wellbeing and service provision decisions of nonprofit hospitals in the years following enrollment into the 340B Program using a staggered difference-in-differences design, based on 20 years (2000–2019) of Medicare Cost Reports and American Hospital Association survey data. Third, I estimate the impact of a 340B Medicare reimbursement cut on nonprofit hospital finances and safety-net spending outcomes, using a triple differences approach, based on cost reports and hospital tax filings.
Prospective assessment of sleep health and reproductive outcomes
(2025) Coleman, Chad Matthew; Wise, Lauren A.
Sleep disturbances and disorders are prevalent in the United States and continue to increase over time. Women often report worse sleep outcomes than men, and these disparities can likely be attributed to both gender and biologic sex. While poor sleep has been associated with many adverse health outcomes, few prospective studies have examined the influence of sleep on reproductive health. Therefore, the goal of this dissertation is to prospectively assess the relationship between sleep health, evaluated through self-reported and objective measures, and three reproductive outcomes: uterine leiomyomata (UL), menstrual cycle disturbances, and fecundability.In the first study, we estimated prospectively the association of self-reported sleep health, including duration and quality, with ultrasound-detected UL incidence and growth. We performed this analysis in the Study of Environment, Lifestyle, and Fibroids (SELF), a prospective ultrasound-based cohort study of reproductive-aged Black individuals from metropolitan Detroit, Michigan. We found that increased frequency of sleep trouble was associated with increased UL incidence rate over 10 years of follow-up. Conversely, short and long sleep durations and feeling well-rested less than half the week were associated with decreased UL incidence rates. Sleep health was not appreciably associated with 18-month standardized UL growth. In the second study, we examined prospectively the association of self-reported sleep health, including duration and quality, and menstrual cycle disturbances. We leveraged data from Pregnancy Study Online (PRESTO), an Internet-based preconception cohort study of non-contracepting pregnancy planners from the United States and Canada. We found that short sleep duration and poor sleep quality increased the risk of several menstrual cycle disturbances, including short and long cycle lengths, prolonged bleed length, heavy menstrual flow volume, and dysmenorrhea. Also, poor sleep quality was associated with greater risk of cycle irregularity. In the third study, we estimated prospectively the association of objective preconception sleep health, including duration, continuity, and irregularity, with fecundability, the per-menstrual cycle probability of conception. For this study, we utilized Fitbit wrist actigraphy data collected in PRESTO to measure sleep health. We observed that short and long sleep durations, increased wake after sleep onset and midpoint variability, and decreased sleep maintenance efficiency were associated with reduced fecundability. Additionally, we found that even if participants slept the recommended duration (7–8.9 hours/day), the association between poor sleep health and reduced fecundability persisted. In summary, we identified associations between sleep health and uterine leiomyomata, menstrual cycle disturbances, and fecundability. We leveraged novel analytic and data collection methods to address our research questions. Given that Healthy People 2030 has highlighted sleep as a priority area for research and intervention, our findings offer valuable insights for developing effective public health strategies. This dissertation underscores the importance of addressing sleep health to potentially improve reproductive outcomes.
Modeling the health and equity impacts of climate action and air pollution control strategies at local, regional, and national scales
(2025) Buckley, Laura; Levy, Jonathan I.
Ambient air pollution poses significant health risks, with extensive research linking pollutants like PM2.5, NO2, and O3 to increased mortality and morbidity. The complex interplay between these pollutants, their sources, and atmospheric dynamics creates challenges for effective air quality management. Moreover, sociodemographic inequities in exposure to air pollution persist across multiple geographic scales, with marginalized communities facing disproportionate burdens due to historical and present-day inequities. Recent technological advancements in remote sensing, chemical transport modeling, and data integration have dramatically improved our ability to characterize air pollution exposure at fine spatial scales, even in areas lacking traditional monitoring networks. This enhanced understanding is crucial as the world grapples with climate change, presenting a unique opportunity to build solutions that simultaneously improve air quality, reduce existing inequities, and mitigate the worst impacts of our shifting climate.This dissertation explores the complex interplay between air pollution, climate change mitigation strategies, and the magnitude and distribution of health equity outcomes through three interconnected studies, each addressing fundamental aspects of air pollution exposure and health risk modeling at different geographic scales. The research examines the health benefits and equity implications of transportation emissions reduction scenarios and vehicle electrification strategies in the United States, while also providing insight regarding the health impacts of NO2 exposure in Mexico. This work collectively provides insight on alternative approaches for air pollution exposure modeling and for characterization of equity, helping to illuminate pathways for designing more impactful, equitable, and health-enhancing policies. In Chapter Two, we explore the equity implications of various transportation emissions reduction scenarios in the northeastern United States, focusing on four distinct equity constructs: racial/ethnic exposure inequities, benefits to environmental justice communities, distribution of benefits among participating states, and rural-urban share of benefits. Using advanced chemical transport modeling, we analyze scenarios for reducing directly emitted fine particulate matter across 12 Northeast states and the District of Columbia, revealing tradeoffs among different equity constructs. Our findings highlight that scenarios resulting in greater reductions in population-weighted primary PM2.5 exposure were generally those centered in states with large urban areas, leading to greater reductions in racial/ethnic exposure inequities but higher between state or rural/urban inequality. Conversely, scenarios targeting uniform percentage emission reductions from trucks better address rural/urban inequalities but lead to smaller reductions in racial/ethnic inequity. In Chapter Three, we evaluate the impacts of vehicle electrification strategies in the Boston metropolitan area of the Northeast United States, focusing on their potential to reduce emissions, improve health outcomes, and address existing exposure and health inequities among racial and ethnic groups. Using high-resolution chemical transport modeling, we examine a set of scenarios targeting different vehicle types within unique regions of the metropolitan area. Our findings highlight that while targeting larger vehicle fleets in suburban areas yielded greater overall health improvements, concentrating efforts on heavy-duty trucks and high-emitting vehicles in urban core areas proved most effective in reducing inequities on a per-vehicle basis. Our findings underline the importance of considering multiple pollutants and utilizing detailed health data in policy decision-making. The final study in Chapter Four assesses the public health burden of NO2 exposure in Mexico, highlighting uncertainties in health impact assessment modeling. This work utilizes two globally modeled ground-level NO2 datasets alongside TROPOMI satellite-derived tropospheric NO2 data to analyze spatial patterns in the pollutant across Mexico and their effects on population exposure estimates and health impact calculations, with different concentration-response functions also evaluated. The analysis reveals tens of thousands of premature deaths annually attributable to ambient NO2 exposure across Mexico annually. The study finds that health estimates vary more with the choice of concentration-response function at the national scale than the exposure dataset, though it is important to note only two exposure datasets were compared. Notable differences emerge between these exposure datasets, however, at the state level, particularly near Mexico City. While demographic patterns are consistent, differences are observed for smaller subpopulations like Indigenous language speakers. This work describes the notable health impacts of NO2 across Mexico, which were previously challenging to define due to limited air monitoring networks. It also highlights the complexities involved in selecting the most appropriate inputs for air pollution health impact assessments at different geographic scales. In conclusion, this dissertation underscores the importance of applying air pollution modeling techniques that fit both the pollutants of interest and the policy context, with heightened importance when considering local or regional contexts. Although the three chapters encompass diverse geographic scales and methodological frameworks, a recurring theme relates to the potential tradeoffs between overall public health improvements and targeted equity gains. Analyses that elucidate these tradeoffs and describe the attributes of policies that perform best across multiple endpoints will be maximally informative. These insights lay a groundwork for future research and policy development that simultaneously address air quality, climate change, and health equity.
Choral conductor perceptions of ensemble success and failure: an application of dimensional attribution theory
(2025) Wittkopp, Jacob Henry; Hendricks, Karin S.
Attribution theory literature provides various ways to discuss the relationships between success or failure and the reasons perceived to be responsible for an outcome. This study is based on Weiner’s (1986) attribution theory of achievement motivation and explores the attributions of choral ensemble performances made by choral directors who work in academic settings. The aims of this research were to determine whether participants’ own successful performances are attributed differently from those they consider unsuccessful and to determine the relationships between attribution responses and personal or work-related differences. An online survey was distributed to collect choral directors’ responses. Participants were asked about their degree backgrounds, the number of years at their current institutions, how many choral ensemble classes they conducted, the size of their institutions’ choral programs, the grade levels of students with whom they worked, whether their institutions were public or private, and demographic self-identifications. The second part of the questionnaire prompted participants to recall their most and least successful choral performances in recent history, then to rate their beliefs regarding 12 statements along a 9-point scale based on McAuley et al.’s (1992) Revised Causal Dimension Scale (CDSII). The statements corresponded to four subscales: locus, internal controllability, external controllability, and stability of the cause they believed most responsible for each prompt. A sample of N = 167 choral directors completed the questionnaire. The sample included choral directors in elementary, secondary, post-secondary, and multiple settings. Reliability testing was particularly poor on one stability test item, which was removed from subsequent analyses. Testing consisted of both parametric and non-parametric tests when applicable. Results from paired Wilcoxon and t-tests both revealed that participants significantly rated attributions of successful and unsuccessful performances differently on three subscales: locus, internal control, and stability. Among the personal and vocational questions, Pearson’s correlation revealed that years at institution negatively correlated with internal control with both success (R = -.220) and failure (R = -.227). The size of choral program was also related to internal control with success according to Spearman’s rho (ρ = -.155). External control with success was also related to level of teaching via Welch’s one-way ANOVA (F = 3.678) and related to public versus private school via independent samples t-test (t = -2.513). Finally, stability with failure significantly varied according to both gender (t = 1.982) and race (t = 02.474). Linear regression was initially used to test which variables could predict each subscale score, but no model produced sufficient R2 values. After converting subscale totals to Z-statistics and reorganizing them into ordinal quartiles, ordinal logistic regression (OLR) produced three modest but statistically significant models for locus with success, external control with success, andexternal control with failure. Alternatively, generalized linear mixed-effect model (GLMM) regression indicate at least one variable as predictive of each dimension for both success and failure. Private versus public institution, level of student taught, size of choral program, and number of ensembles appeared to predict more than one subscale. Limitations and concerns with the instrument and data are subsequently addressed. Discussion includes implications for how choral ensemble leaders might more intentionally reconsider the possible reasons for their own performance disappointments and how they convey those reasons to others. Results may additionally help those who serve in mentorship or adjudication capacities. Directions for future research are also offered.
Domenico Dragonetti and his twelve waltzes: sexuality and the double bass
(2025) Granger, Jacob; Yudkin, Jeremy; Melchor-Barz, Gregory
Venetian double-bass virtuoso Domenico Dragonetti (1763–1846) had a significant hand in establishing the double bass as a strong and capable ensemble and solo instrument. As with many virtuosos of his time, Dragonetti was often described by his associates as eccentric and bizarre. In fact, many aspects of his personal life seem enigmatic and strange. One of the least understood aspects of Dragonetti as a person is his sexual identity. He remained a bachelor his entire life and seemed not to pursue any sexual or romantic relationships. Instead, he referred to his double bass as his “wife.” To make sense of this sexual ambiguity, I have deployed contemporary theories on gender and sexuality in an attempt to unearth a more descriptive sexual identity for Dragonetti. Through analysis, I argue for a possible asexual and aromantic identity. To explore the relationship Dragonetti had with his bass, I analyze what is believed to have been one of Dragonetti’s last compositions, a set of twelve unaccompanied waltzes for double bass. These compositions seem to have been very personal to the virtuoso and were only heard by a single, close friend, Vincent Novello. The waltzes seem to be private and personal engagements between Dragonetti and his “wife.” By analyzing the inner workings of these dances, I aim to gain a better understanding of Dragonetti’s sexual and romantic orientations as well as his relationship with his beloved double bass.
Using digital clinical simulations to support early career teachers’ sensemaking about ambitious and equitable mathematics teaching
(2025) Barno, Erin; Dietiker, Leslie
This dissertation investigates how early career teachers' orientations of students and their mathematical activity, as surfaced their experience in a simulation, can reveal when their well-intentioned decisions might negatively impact traditionally underserved students. Three early career teachers engaged in two online simulations where they could speak, write, or select a response to a classroom scenario described with text and images, where their choices impact what part of the scenario they engage with next. The simulations were designed to elicit a tension between the teachers’ intended positive orientations about students and their decisions made in the simulations. A narrative analysis (Slocum-Bradley, 2010; Wortham, 2001) of the participants’ choices in the simulations, and their rationale behind those choices, revealed multiple instances where the teachers aligned themselves with the same orientations but sometimes positioned their role as teachers in conflict with that orientation. The narratives that emerged regarding these specific moments, the teachers' interpretation of that moment, and their decisions in the simulation showed multiple ways the rationalization of decisions can conflict with their intention. This dissertation informs how making sense of the narratives early career teachers make when engaging with simulations could help teachers' interpretations and actions better align with their intentions. Therefore, teacher learning could shift from focusing on content knowledge, pedagogical content knowledge, and pedagogical choices to the continual attention and decision-making around the interpretation that supported that decision.
Cortical function, gait alterations, and central sensitization in people with knee osteoarthritis
(2025) Lee, Soyoung; Kumar, Deepak
For healthy individuals, walking is an automatic locomotion. However, for people with knee osteoarthritis (OA) who often have chronic knee pain and reduced physical function, walking can be less automatic movement that accompanies altered patterns and requires fine motor control. Over-recruitment of the prefrontal cortex (PFC), a region of executive function, during walking can be the underlying neurobiology of disrupted gait automaticity. Therefore, the aim of the Study 1 was to determine the association between the over-recruitment of PFC and altered gait patterns in single- and dual-task walking paradigms. We found that higher activation in subregions of PFC is associated with low variability in step duration (better gait automaticity) during dual-task walking in people with knee OA. In Study 2, we investigated whether the presence of central sensitization, a major biological cause of chronic knee pain, is related to the over-recruitment of PFC and the loss of gait automaticity. Since central pain sensitization involves alterations in activity and connectivity across multiple brain regions, including PFC, central sensitization could be one mechanism by which chronic pain leads to plasticity in brain function and less automatic gait patterns. Study 2 has found that people with a low-pressure pain threshold (PPT) at the unaffected joint (indicating the presence of central sensitization) show greater activation in subregions of the PFC and higher stride length variability (worse gait automaticity) compared to those with a high-PPT during walking. Overall, these findings suggest that people with knee OA may require greater executive control through PFC modulation during complex walking conditions to maintain gait automaticity. Additionally, Study 2 suggests that individuals with knee OA and central pain sensitization may need enhanced executive control during walking compared to those without, highlighting central sensitization as a potential therapeutic target for restoring normal walking function.
Shadow Cathedral
(2025) Lim, Joogwang; Fineberg, Joshua
In Shadow Cathedral, the listener is invited to step into an inverted place—a cathedral not of stone and glass, but of shadow and abstraction. This imagined space resounds not with the shining lights and echoes of people, but with the acoustic and psychological reverberations of solitude. As one might hear an empty chapel "sing" in its stillness, the music seeks to evoke a deeply personal, introspective, and raw resonance. Shadow Cathedral draws inspiration from the Adagio movements of late Romantic symphonies, whose slow, expansive passages evoke a sense of timeless contemplation. However, instead of using traditional triadic harmonies, this piece presents raw “sound icons”—bells, chants, and drums—that serve as focal points around which the music orbits. These icons guide the listener toward moments of ferocious self-exposure, reflecting the composer’s own vulnerabilities. Shadow Cathedral is a meditation on the power of emptiness—a sonic journey that discovers sublimity in raw human expression and the transformative nature of solitude.
Image reconstruction through multiple 1D approximations
(2025) Wang, Bohan; Considine, Jeffrey
Function approximation is a fundamental aspect of computational models and machine learning, often relying on neural networks due to their ability to effectively model complex functions and relationships. However, neural networks can be computationally intensive and lack interpretability. In this thesis, we explore an alternative approach to approximating two-dimensional (2D) functions by decomposing them into multiple one-dimensional (1D) approximations. Our method aims to enhance computational efficiency and interpretability while maintaining high approximation quality. We propose a framework that projects to approximate 2D functions through a series of 1D interpolations and also uses greedy sampling. By generating uniformly distributed projections and projecting pixel coordinates onto these projections, we form 1D curves and use interpolation to predict the values of the original function. Linear interpolation is employed for its simplicity and speed in estimating values between sampled points. A greedy algorithm is used to select sampling points that significantly reduce approximation error, optimizing the sampling strategy. We conducted extensive experiments on some images to evaluate the performance of our method. Metrics such as Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) were used to assess reconstruction quality. Additionally, we ran neural network model and some other traditional models for comparison. Our results demonstrate that the proposed method provides a different focus compared to other methods, especially excelling in the restoration of high-contrast details in images. The findings suggest that multiple 1D approximations can reconstruct 2D functions with efficiency. Contrary to our initial intuition, the results reveal that increasing the number of sample points has a more significant impact on reconstruction quality than increasing the number of projections. Specifically, we observed that under the same parameter count, using as many sample points as possible led to better reconstruction results. Increasing the number of projections, while beneficial for reducing artifacts, has a less pronounced effect compared to increasing sample points. However, adding more projections can improve edge clarity and enhance the accuracy of each step in the greedy selection process, which helps in achieving better sample point locations during reconstruction. Additionally, we tested various sampling methods, such as uniform sampling and greedy MSE selection, and found that greedy selection of sample points based on MSE yielded significantly improved clarity, particularly around key features of the image. The experiments also showed that incorporating spatial diversity and edge information into the selection process did not always yield better results, highlighting the importance of selecting sample points that balance both edge and surrounding details. This work contributes to the field by providing an alternative method for function approximation that addresses some limitations of neural networks, particularly in terms of computational efficiency. Future work includes extending the approach to higher-dimensional data, exploring advanced interpolation techniques, and integrating the method with machine learning models to balance performance and transparency. Additionally, further research is needed to optimize the balance between projections and sample points to achieve the best reconstruction quality under different parameter constraints.
“He Cares About All of Us”: nine middle school chorus students’ lived experiences with teachers as carers
(2025) Bauman-Field, Betty; Goodrich, Andrew M.
Music educators value positive, caring relationships with their students. In large ensemble classes, however, music teachers have historically prioritized the needs of the group over the needs of individuals, making it difficult for music teachers to give students the individual attention often associated with caring relationships. If students do not feel that their needs are met, they may not believe their music teachers care for them. Noddings’s (2013) care ethics served as the theoretical framework for this study. The purpose of this study was to understand how middle school chorus students perceive their chorus teachers as carers and what actions, if any, they believe their chorus teachers take to make students feel cared for as individuals. I engaged in hermeneutic phenomenology to examine the essence of caring relationships in middle school chorus from the perspective of the students. I conducted semi-structured interviews with three eighth grade chorus students from each of three middle schools for a total of nine student participants. I analyzed the data using in vivo coding to prioritize students’ thoughts and beliefs about the ways in which their chorus teachers demonstrated care. Once the data were coded, I themed codes phenomenologically using “Caring is…” as a sentence starter. The middle school chorus students in this study felt cared for when their chorus teachers created positive classroom environments by including and welcoming all students, providing a social space, supporting student safety, and encouraging teamwork and participation; listened and addressed individual needs; taught effectively; demonstrated certain personality traits, such as being fun, kind, and enthusiastic; and deepened connections with students over time. I determined that in many instances, the behaviors students identified as caring were group-oriented behaviors, suggesting that individual participants felt cared for by their chorus teachers when caring behaviors were demonstrated toward the group rather than between a teacher and individual student. Additionally, none of the participants described feeling that their teacher did not care about them, further indicating that individual students in this study felt cared for despite the large group setting of a middle school chorus. Although there may be benefits to prioritizing caring interactions with individual students when possible, findings from this study suggest that middle school chorus students perceive group-oriented behaviors, such as establishing a positive classroom environment, engaging in high quality instruction, and presenting a kind and humorous demeanor, to be ways in which their teacher demonstrate care.
The orphaned subject and moral debilitation: accounting for postcolonial pessimism
(2024) Hong, Hyebin; Fluker, Walter E.; Rambo, Shelly
This dissertation investigates the concept of “moral debilitation” as it pertains to the “orphaned subject” in Korean society, a notion that denotes the diminished moral agency consequential to colonial and neocolonial legacies. The term “orphaned subject” describes certain characteristics prevalent among a group of contemporary Koreans characterized by moral debilitation due to the enduring sense of dislocation and psychological distress. The author traces these characteristics through literary representations, notably the motif of the “orphan consciousness” and the recurring depiction of the absent Father figure in modern Korean literature. This dissertation maintains that acknowledging and addressing the compromised moral agency of the colonized is essential for postcolonial theological analysis. This approach reveals how colonial harms extends beyond the material, political, economic, and psychological realms to affect the moral constitution of the colonized subject. The author posits this pessimistic account of moral debilitation not as an indictment of the colonized but as a means to a deeper, more integrated comprehension of the postcolonial condition.
Adapting to a warming climate: electricity demand, air conditioning, and the health impacts of extreme heat
(2023) Romitti, Yasmin; Sue Wing, Ian
The increasing incidence and intensity of days and spells of extreme heat is expected to continue with climate change, with interconnected and cascading consequences across multiple scales and sectors. In particular, high temperature exposures directly affect population health (e.g., increased risk of hospitalization and death) and cooling energy demand (i.e., the use of residential air conditioning (AC) as adaptation). Heat extremes are often amplified in urban areas due to the thermodynamic properties of the built environment. While we have a strong understanding of the relationship between heat and energy demand, energy and AC, and the impacts of heat on morbidity and mortality, there remain notable knowledge gaps in the dynamics that underpin these relationships, and only a handful of studies are able to explore their linkages together, especially at fine spatial scales. In this dissertation, I combine econometric and epidemiological methods to provide further insights into several dimensions of the intersection of heat, electricity, AC, and health in urban populations, and holistically assess these linked relationships together. In my first chapter, I characterize the response of urban electricity demand to temperature at fine temporal resolution across a subset of world cities, and quantify the impacts of future heat adaptation on net and peak energy demand under mid-century warming. Temperature-demand response functions and future demand impacts are heterogeneous across temperate and tropical cities, highlighting the important role that the structure of electricity demand plays alongside distributional temperature shifts in evaluating the impacts of climate change on future energy demand. In my second chapter, I construct fine spatial resolution estimates of any residential AC across a large set of US metropolitan areas. Inter-urban availability of AC exhibits a strong latitudinal gradient, while intra-urban AC is systematically unequally distributed within cities. This inequality is also negatively correlated with social vulnerability (SVI) and surface urban heat island intensity (SUHI), suggesting that differential AC compounds existing heat health disparities. In my third chapter, I additionally compute individual and ZCTA-level estimates of AC use on extreme heat days alongside individual probability of AC in California cities, and evaluate the differences in the moderating effects of these related attributes of heat vulnerability on heat-related hospital admissions. AC prevalence and AC use are correlated, but both measures of adaptation are only weakly correlated with social vulnerability within cities. The spatial distribution of health risks from extreme heat echoes spatial patterns of increasing social vulnerability, and both AC prevalence and use significantly modify the association between extreme heat and a number of health outcomes. However, effect estimates differ between AC prevalence and AC use, suggesting that AC ownership does not necessarily reflect AC usage, and, crucially, that there remain additional unobserved dynamics driving the heat-adaptation-health relationship. Identifying the underlying factors and determinants of population heat health vulnerability at the local scales in which impacts and adaptation decisions take place is necessary as cities and municipalities develop and refine heat resilience policies and climate adaptation strategies aimed at reducing heat health inequities and improving community well-being.
Forecasts from the deep past: using paleoclimate analogues to inform climate projections
(2023) Watkins, Aja; Bokulich, Alisa N.
This dissertation lies at the intersection of philosophy of climate science, philosophy of the historical sciences, philosophy of model-based science, and philosophy of data. I focus on epistemological and methodological issues concerning how scientists use episodes of climate change in Earth’s deep past that significantly resemble incipient climate change ("paleoclimate analogues") to inform their climate projections. I argue that we should conceptualize paleoclimate analogues as kind of climate model - a naturally-occurring, full-size, concrete model – and that viewing paleoclimate analogues through this lens has important philosophical implications. It follows, for instance, that the usefulness of models does not depend on our ability to experimentally manipulate them (we cannot manipulate the deep past). I also argue that the historical sciences can be predictive: they can use the past as a guide to the future. I give several recommendations for scientists, including some guidance on how to manage, process, and evaluate paleoclimate data in order for it to be used to inform our climate projections, despite various sources of error and uncertainty inherent to our reconstructions of the deep past. I close with some general reflections on "using the past as a guide to the future," within the context of paleoclimate analogues and beyond.
Maker music: constructing musical knowledge in educational makerspaces
(2025) Hable, Burton William; O'Leary, Emmett J.
The purpose of this study was to develop evidence for how students could construct musical knowledge in educational makerspaces and to inform alternative pathways to musical knowledge. Makerspaces are places where tools and technologies are available for people of varying ages and skill levels to engage in constructing and sharing of physical or digital artifacts (Sheridan et al., 2014). Educational makerspaces are specifically designed for learning to take place through making (Harron & Hughes, 2018). Makers learn through the making and sharing of personally meaningful artifacts (Sheridan et al., 2014) by constructing knowledge through the processes and products of making (Papert, 1980/2020). Makers learn concepts and skills across multiple disciplines, primarily in the fields of science, technology, engineering, arts, and mathematics (STEAM; Brahms & Crowley, 2016b; Clapp & Jimenez, 2016). Empirical research demonstrates that makers also learn concepts and skills within arts disciplines, but more evidence is needed of makers engaging with arts disciplines or constructing arts knowledge through making. In this dissertation, I conducted a holistic multiple case study (Yin, 2018) of two participants' work in two educational makerspaces. I used bi-directional artifact analysis methods to construct timelines and narratives for how participants conceived of, constructed, and shared musical artifacts (Halverson & Magnifico, 2013). Participants used the tools, technology, expertise, and environment of the educational makerspaces to engage with music by playing physical and digital instruments, interacting with a community of musicians for collaboration and feedback, and sharing musical works through performance and distribution. By engaging with music, participants also engaged with interdisciplinary STEAM concepts with parallel concepts in music. Ultimately, participants constructed knowledge of music concepts by using maker resources to create musical artifacts. Maker music—when people construct musical knowledge by engaging in maker activities within the domain of music—is a meaningful and compelling way to learn music. The participants in this study demonstrated maker music by creating and releasing original music and developing skills as music producers. The makerspaces in this study provided opportunities for participants to follow representational trajectories—learning the skills and tools for realizing ideas (Halverson, 2021)—as music producers and creators. The participants' musical artifacts demonstrate how maker experiences can provide deep musical experiences that engage multiple disciplines.
The fundamentals of genome-scale metabolic models and their application to the study of evolution and cancer
(2025) Moyer, Devlin; Fuxman Bass, Juan I.
Hundreds to thousands of distinct metabolic reactions occur in all cells, forming a densely interconnected metabolic network that transforms similarly numerous metabolites into each other. Genome-Scale Metabolic Models (GSMMs) encode all existing knowledge about the structures of these metabolic networks, the enzymes responsible for catalyzing their reactions, the genes that encode those enzymes, and the metabolites that they interact with. Integration of different forms of high-throughput data within a single GSMM has facilitated numerous biological insights, ranging from strategies for engineering the metabolisms of microbes to produce commercially and/or medically valuable compounds to identifying novel drug targets for cancer, diabetes, inborn errors of metabolism, infectious diseases, among others. Due to the complexity of cellular metabolic networks and the limited availability of relevant experimental data, the predictive utility of GSMMs is often limited by missing or inaccurate reactions. Furthermore, common approaches to predicting metabolic fluxes from GSMMs often focus on identifying a single optimal flux state, which frequently leads to inaccurate predictions for specific cell types or disease states where biologically plausible metabolic optima are unknown or challenging to formally define. This dissertation addresses several limitations of existing approaches to creating and using GSMMs, with particular emphasis on the following challenges: (i) testing for the presence of reactions which can sustain unrealistically high fluxes, duplicate reactions, and missing or misannotated reactions; and (ii) predicting biologically and statistically sound distributions of steady-state fluxes through GSMMs, including methods which involve the incorporation of transcriptomics and/or proteomics data from particular conditions, which are especially relevant for the development of tissue-, disease- and patient-specific GSMMs. In addition, I extend the techniques for predicting fluxes through GSMMs to artificial chemistry networks — abstract models of simplified chemical reaction networks, which have been used to study general principles governing the behavior of such networks while avoiding the incompleteness of our understanding of real biochemistry. Specifically, I use these artificial chemistry networks to study general principles governing the evolution of the structures of metabolic networks, and demonstrate the importance of the biomass composition in determining intracellular network architecture. Throughout the dissertation, I present multiple tools and recommendations for improving the predictive quality of GSMMs and demonstrate their utility by correcting several hundred errors in the most recent GSMM of generic human cells, with possible broad implications for the field of metabolic modeling and its applications.
Two essays on empirical asset pricing
(2025) Wei, Fanwei; Vedolin, Andrea
This dissertation consists of two papers on asset pricing. The first paper constructs a new framework based on recombinant tree structure to recover asset price distributions and associated discount factors from state price information. The recoveryframework is compatible with common price process and utility assumptions. The recovered results are closely aligned with data observed from market. The second paper uses Gibbs sampler to estimate the transaction costs from price impact in addition to bid-ask spread, and re-examines anomaly profitability after newly estimated TC. Cost mitigation methods and maximum market capacity with mitigation techniques are also studied for each anomaly. TC from both spread and price impact rules out most acclaimed anomalies. However, proper cost mitigation methods can restore their profitability.
Characterizing cell-type and neuron subtype activity and abundance in asymptomatic Alzheimer disease
(2025) O'Neill, Nicholas Kerry; Zhang, Xiaoling; Farrer, Lindsay A.
Alzheimer’s disease (AD) is a progressive and complex neurodegenerative disorder characterized by increasing amyloid-β (Aβ) plaque burden, followed by increasing neurofibrillary tau tangles (NFT) and cognitive decline. However, many individuals fall outside of this typical progression, either exhibiting NFTs without Aβ or maintaining cognitive performance despite the presence of AD pathology, i.e., cognitive resilience. AD progression is also associated with changes in cell-type abundance and cell-type-specific activity. This dissertation investigates these topics by integrating AD brain single-nuclei RNA-seq (snRNA-seq) with large-scale bulk RNA-seq datasets and whole genome sequencing datasets generated from the same individuals. We developed an algorithm for bulk cell-type deconvolution using a snRNA-seq reference dataset by adjusting for technical differences specific to snRNA-seq. We then applied this algorithm to examine the relationship between cell-type abundance and AD endophenotypes, including cognitive resilience, in brain regions that are vulnerable or resistant to the disease. In addition, we identified and discussed genetic drivers of changes in cell-type abundance. Finally, we generated highly cell-type-specific AD polygenic risk scores (ct-ADPRS) to investigate the relationship between cell-type activity and AD progression.

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