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Fluency in Oral and Silent Reading: Creating a Balanced Foundation for Reading Comprehension
No full textFluency is a critical skill in many theories of reading development. This is because a hallmark of fluency—automatic word recognition—is theorized to facilitate the ability to read grade-level text with comprehension. Too many US children, however, are struggling to demonstrate adequate levels of fluency in oral and silent reading, and ultimately to comprehend grade level texts. Consequently, critical theoretical and practical questions for the field are: what text-matching approach is most effective for improving young children’s reading fluency, what levels of fluency are needed to succeed on grade-level reading comprehension tests, and where should educators focus to ensure children matriculate with the fluency skills needed to undergird grade-level reading comprehension? This dissertation responds to these questions in three thematically related papers that address the role of fluency in children’s reading comprehension. Paper 1 meta-analyzes the literature on fluency interventions to consider whether children should practice with texts that align to their grade level or to their individual ability. It compares the benefits of exposure to grade-level versus reader-matched texts. Paper 2 examines the role of fluency during silent reading and investigates the relationships between silent reading rate, stamina, and reading comprehension. It provides important insights pertaining to adequate fluency in the silent mode, which is essential for success on silent reading comprehension tests. Paper 3 integrates the findings in the first two papers and offers a practical guide to educators who provide targeted reading intervention support. It presents a revised model for identifying the primary need in reading intervention, explicitly attending to silent reading rate and stamina, and provides recommendations for supporting silent reading comprehension in Grade 3. Together, these studies increase our understanding of the factors that influence fluency acquisition in oral and silent contexts. In doing so, they contribute to our understanding of how to create a balanced foundation for reading comprehension and support children who fail grade-level silent reading comprehension tests due to inadequate fluency.Educatio
Interpreting the Qurʾān in the Islamic West (7th – 11th c.): Tradition and Transformation in Tafsīr
No full textWhile it has long been understood that the Qurʾān was central to the religious, intellectual, and cultural life of Muslims in both the medieval Islamic West and the East, the local history in the western Islamic lands of tafsīr – formal Qurʾānic exegesis – has been all but ignored by modern scholars. This dissertation illuminates the development of this genre in the Maghrib (both North Africa and the Iberian Peninsula) in the earliest period, the age prior to the Almoravids. It examines unique regional schools of thought as well as the connections of Western authors with the cities, scholars, and intellectual fashions that arose elsewhere in the Islamicate world. Far from a backwater, the exegetes of the Islamic West are shown to have intimate knowledge of scholarly developments elsewhere, although (at least in this period) that interest was not shared reciprocally. Simultaneously, the dissertation traces how novel theo-political movements – such as the Ibāḍī principality of the Rustamids that ruled from Tāhart, or the Ismāʿīlī Fāṭimids who swept across North Africa at the end of the 3rd hijrī century – produced exegetical reflections profoundly shaped by the regionally-specific interplay between ‘official’ ideology and the characteristic inertia of exegetical tradition. The dissertation concludes with the growth of a newly professionalized class of scholars and its effect on tafsīr, as new compositions were penned with the express purpose of offering students introductory ‘textbooks’ that epitomized the field’s key scriptural insights. With the collapse of Umayyad rule in al-Andalus, the rise of the Ṭāʾifah kings of the 5th/11th century, and the resulting investment in linguistic knowledge as a central facet of the sovereign’s courtly prestige, this period was marked by a melding of traditional commentary with philology that the dissertation terms “the linguistic turn.”
Chapter 1 offers a critical overview of the earliest moments of Qurʾānic reflection in the Islamic West. It shows that while specific local tafsīr of this period does not survive, the social infrastructure for formal exegesis began to be developed, above all in the newly-founded metropolis and regional lodestar of Qayrawān.
Chapter 2 examines the two oldest ‘Western’ mufassirs whose commentary survives, Yaḥyā b. Sallām (d. 200/815) and ʿAbd Allāh b. Wahb (d. 197/813). Where the latter represents an extremely ancient exegetical style – a compilation of disparate traditions, narrated from individual masters – the former, who would become the central interpreter of the emerging Maghrib, demonstrates the transition to sequential, book-format commentary that transformed the genre.
Chapters 3 and 4 cover the exegetical innovations of the 3rd-4th/9th-10th centuries in North Africa and al-Andalus, respectively. Chapter 3 pays particular attention to the effect of official theo-ideologies on tafsīr, considering the hermeneutic implications of Ibāḍī and Ismāʿīlī thought as well as the tradition of Sunnī interpretation that continued under the new Fāṭimid rulers of Qayrawān. Chapter 4 offers a series of scholarly portraits, showing the striking diversity within Andalusī commentators of this period. Even as many of their texts have been lost, the chapter reconstructs significant elements of their thought through an archeology of later sources. It then concludes with the still-extant commentary of Ibn Abī Zamanīn, whose philologically-atuned abridgment of Ibn Sallām’s tafsīr encapsulates the ‘mukhtaṣar moment’ of Andalusī exegesis.
Chapter 5 takes up two North African commentators who both moved to al-Andalus in the early 5th/11th century, Makkī b. Abī Ṭālib al-Qaysī and Abū al-ʿAbbās al-Mahdawī. Both were better-known as reciters (muqriʾs), and their commentaries reflect a consistent focus on questions of scriptural language, including the place of linguistic issues in other fields such as theology or law.Near Eastern Languages and Civilization
Genetic and Evolutionary Basis of Behavioral Variability in Drosophila melanogaster
Get PDFBehavioral individuality is a ubiquitous phenomenon. Animals from genetically homogeneous populations reared in identical environments display persistent and variable behavioral phenotypes. This behavioral variability can be heritable and potentially adaptive through a bet-hedging strategy, wherein genotypes that produce a range of behavioral phenotypes enhance their long term fitness in unpredictably fluctuating environments by increasing the probability that some individuals will express traits well-suited to the current conditions. In this dissertation, I investigate the genetic and evolutionary basis of behavioral variability in Drosophila melanogaster, combining theoretical modeling with experimental approaches to test its evolvability and underlying mechanisms.
In Chapter 1, I develop a computational model to examine how variability responds to artificial selection. I compare family-based and individual-based selection strategies and show that family-based selection, where variability is measured across related individuals, is more effective than individual-based selection when the trait under selection is variance-based but not when it is mean-based. I further explore how population size, genetic architecture, and selection strength shape
evolutionary outcomes.
In Chapter 2, I apply these insights in a 21-generation artificial selection in fruit flies experiment targeting increased variability in locomotor handedness. I observe a consistent increase in behavioral variability over selection without a shift in mean turning bias. This evolved variability is polygenic and potentially has some sex-linked basis. I also identify changes in central complex morphology and correlated tradeoffs in mating success.
In Chapter 3, we shift focus to thermal preference, an ecologically relevant behavior. Using a panel of inbred lines, we show that the mean and variability of thermal preference are both heritable, and genetically independent. Genome-wide association implicates spag, a co-chaperone of Hsp90, as a regulator of thermal preference variability.
In Chapter 4, we investigate the genetic basis of the offspring number–body weight tradeoff using a composite offspring index. We identify candidate genes influencing this tradeoff and demonstrate through functional experiments that specific mutations alter the balance between offspring size and number.
In the concluding chapter, I outline future directions, including experimental evolution approaches for studying bet-hedging. Together, this work shows that behavioral variability is an evolvable trait shaped by genetic and neuroanatomical factors.Biology, Organismic and Evolutionar
Statistical Methods for Improving Real-Time Outbreak Detection
Get PDFReal-time outbreak detection in resource-constrained settings requires robust statistical methods that can account for aberrations in historical data, reporting delays in the most recent observations, and dynamic changes in transmission trends. This dissertation develops and evaluates outbreak detection frameworks that address these practical challenges using simulation-based evaluation, real-world data applications, and flexible statistical modeling.
Chapter 1 investigates the impact of historical anomalies—termed ``aberrations''—on the performance of rolling outbreak detection methods applied to health management information system (HMIS) data. Motivated by five years of acute respiratory infection (ARI) surveillance data from Liberia, we simulate outbreaks under seven distinct data-generating mechanisms varying in trend and seasonality. We assess five detection algorithms: EARS, Farrington, Holt-Winters, and two Weinberger-Fulcher (WF) models (negative binomial and quasipoisson). Detection accuracy is measured through sensitivity, specificity, and pseudo-ROC curves, under varied aberration timing and outbreak size. We find that the presence of recent aberrations in the baseline degrades performance across models, with context-specific tradeoffs: EARS and WF models perform well in the absence of recent anomalies; WF QP and Holt-Winters maintain better balance between sensitivity and specificity when recent aberrations are present; and Farrington achieves high sensitivity but lower specificity in these settings. These results offer practical guidance for selecting rolling detection models under imperfect baseline conditions common in low- and middle-income countries (LMICs).
Chapter 2 develops a novel frequentist framework for real-time nowcasting of all-cause mortality under reporting delays, using Massachusetts death registration data from 2017 to 2022. Reporting delays are modeled via a discrete-time survival model that incorporates covariates such as day of the week, lag, and snapshot date to flexibly capture evolving delay patterns. Using method-of-moments estimation, we correct underreported death counts, propagate delay uncertainty into variance estimates, and apply LOESS smoothing to stabilize predictions for the most recent days. Variance from both the delay model and smoothing step is incorporated into predictive intervals. Compared to leading Bayesian and spline-based nowcasting methods, including hierarchical Bayesian models, NobBS, EpiNowcast, and GAM approaches, our method achieves superior empirical coverage, lower bias, and narrower interval widths, particularly during the early pandemic phase when reporting delays exhibited sharp day-of-week effects. Explicit modeling of day-of-week reporting behavior substantially improved accuracy relative to approaches that omitted temporal covariates, and the method remained robust to shifts in the reporting distribution across time.
Chapter 3 extends this delay correction framework by integrating nowcasting with slope-based outbreak detection in a unified two-stage approach. Using molecular-confirmed COVID-19 case data from Puerto Rico, we estimate unreported cases via a discrete-time hazard model and then fit a slope-based detection model using generalized estimating equations (GEE), incorporating nowcast-derived variances as observation-level weights. We conduct a simulation study varying epidemic wave intensity, reporting delay speed, and baseline structure---including both stable and declining post-wave baselines---to evaluate time to detection, false positive rate, and calibration across models. We benchmark against the Farrington algorithm, -based detection, and the Weinberger-Fulcher model. Our slope-based GEE approach consistently achieves faster and more reliable detection, particularly under low and medium wave scenarios with reporting delays, while maintaining strong calibration across a range of nominal alpha levels. The method also performs well when applied to real-world Puerto Rico data, issuing timely signals across three distinct epidemic waves.
Together, these chapters provide a comprehensive statistical toolkit for outbreak detection under the operational constraints of incomplete, delayed, and aberration-prone surveillance data. The approaches developed are computationally efficient, modular, and applicable across diverse epidemiological contexts, with particular relevance for LMICs and subnational surveillance systems.Biostatistic
Chemical microscopy and image analysis for biomedical applications
Get PDFChemical microscopy enables the identification and spatial analysis of chemical composition within a sample, offering powerful insights across a range of applications. This dissertation demonstrates the capability of chemical microscopy tools in diverse settings, from solid pharmaceutical materials to living organisms to human subjects in a clinical environment. The overarching principle guiding these studies is that, for simpler static samples, highly complex imaging techniques can be employed to extract rich chemical detail, whereas, for complex, dynamic biological systems, faster, more mobile tools, complemented by computational analysis, become essential.
The progression of this work begins with the application of high-resolution coherent Raman microscopy to analyze well-defined, abiotic samples, demonstrating its ability to rapidly visualize and quantify chemical components in solid pharmaceutical tablets. Extending this approach to biological systems, the technique is then applied to measure the uptake of cryoprotective agents in Daphnia in correlation with toxicity, a critical step towards improving the development of cryopreservation protocols. These studies illustrate how chemically specific imaging can enhance material characterization and biological assessment, while also highlighting the increasing challenges of applying sophisticated tools to living systems.
As the complexity of the sample increases, so do the demands on imaging methodology. In human subjects, where motion, heterogeneity, and physiological variability complicate data acquisition, a shift toward simpler, more mobile imaging modalities combined with computational approaches becomes essential. We use a cart-based multiphoton microscopy tool to characterize atopic dermatitis in humans in vivo, integrating imaging with spatial transcriptomics to improve our understanding of how RNA expression correlates with cellular level features. Further, the use of machine learning with these microscopy images enables disease classification and severity prediction, with the ultimate goal of replacing biopsies during longitudinal clinical studies of skin disease.
Through this progression from controlled, static samples to complex, dynamic systems, this dissertation illustrates both the power and the limitations of chemical microscopy across diverse applications. Ultimately, this work contributes to the advancement of chemical microscopy as a versatile, noninvasive tool for biomedical and translational research.Biological and Biomedical Science
In Vitro Oogenesis: High-Throughput Epigenetic Screening for Efficient Derivation of Human Germ Cells and Meiotic Induction from induced Pluripotent Stem Cells (iPSCs)
Get PDFIn vitro gametogenesis—the development of artificial gametes from pluripotent stem cells—represents a promising approach in reproductive biology with potential implications for understanding infertility, which affects approximately 15% of couples worldwide. While significant progress has been made in mouse models, human in vitro oogenesis has remained challenging due to species-specific differences in germ cell development, complex epigenetic requirements, and technical limitations in recapitulating meiosis outside the body. This thesis explores an integrated approach to address some of these challenges through transcription factor-directed differentiation, epigenetic modulation, and live imaging techniques.
We first develop a protocol for inducing human oogonia-like cells (iOLCs) from induced pluripotent stem cells (iPSCs) through systematic screening of germline-associated transcription factors. We identify a combination of five transcription factors—ZNF281, LHX8, SOHLH1, ZGLP1, and ANHX (termed the D5 cocktail)—that enhances DDX4+ iOLC yield when combined with DNA methyltransferase inhibition. These iOLCs express key germline markers, maintain proliferative capacity, and can be maintained feeder-free after isolation, offering an alternative to conventional methods that typically require months of culture in complex environments.
Building on this foundation, we investigate the more challenging aspects of meiotic induction. Through a combination of DNA demethylation, retinoid signaling, and overexpression of specific factors (BCL2, HOXB5, and BOLL), we observe expression of early meiotic markers and progression through initial meiotic stages. Single-cell RNA sequencing coupled with computational analyses—including gene regulatory network inference, pseudotime trajectory modeling, and barcode-linked factor enrichment—enables us to map the transcriptional landscapes of differentiating cells and identify key regulators of meiotic commitment.
To directly visualize these dynamic cellular processes, we develop CRISPR-mediated knock-in reporter lines for synaptonemal complex proteins using the fluorescent protein mStayGold. Our integrated computational framework leverages deep learning-based cell segmentation, trajectory tracking algorithms, and feature extraction to analyze complex temporal patterns in high-dimensional imaging data. This computational pipeline enables quantitative characterization of protein localization dynamics and cellular transitions during meiotic progression that would be undetectable through traditional analytical approaches.
This work contributes to ongoing efforts to model aspects of human oogenesis in vitro and offers potential insights into the regulation of germ cell specification and meiotic entry. While substantial challenges remain in achieving complete meiosis and functional oocyte formation, the approaches described here may provide tools for studying fundamental aspects of human reproduction, exploring factors that influence fertility, and investigating genetic components of reproductive development. Computer Scienc
The Language of Lesbian Lyric: Local Tradition and Epic Influence in Sappho and Alcaeus
No full textThis dissertation provides a comprehensive reassessment of the poetic language of the two Lesbian poets, Sappho and Alcaeus. Their poems are still widely considered to mostly reflect the spoken Lesbian dialect of the day, with minor epic intrusions. This view contrasts with our current understanding of the dialects of Greek poetry as formalized literary languages, grounded in but not identical to the spoken dialects of Greek and associated with specific poetic genres. How we conceive the language of Sappho and Alcaeus affects how we reconstruct the poetic tradition that preceded them and more broadly the relationship between Lesbian lyric and epic poetry.
This dissertation analyzes the language of Sappho and Alcaeus focusing on traits guaranteed by the meter to show how linguistic variation was inherent to how they composed. Chapter 1 examines the developments internal to the Lesbian dialect that the poets exploit for metrical flexibility. Chapter 2 focuses on borrowings into the diction of Lesbian poetry that we can trace to Ionic and epic poetry. Chapter 3 discusses the overall distribution of this evidence in the corpus of the two poets and how it informs our perspective on the existence of a local Aeolic tradition of poetry in Lesbos before Sappho and Alcaeus and its relationship with epic poetry, using Sappho 44 (the wedding of Hector and Andromache) as case study.
In particular, this dissertation argues for the existence of native processes of metrical lengthening and metrical shortening within the poetic diction of Sappho and Alcaeus. The availability of these artificial processes—alongside archaisms—to both Sappho and Alcaeus points to a long-standing poetic tradition in Lesbos. At the same time, the quality and distribution of epic borrowings in Sappho and Alcaeus’s poetry suggests both active engagement and deep familiarity with the compositional grammar of epic poetry. Ultimately, this dissertation argues that the language of Lesbian lyric is a formalized literary language, with links to both an older, lost tradition local to Lesbos and epic poetry. Both Sappho and Alcaeus show their mastery of this linguistic medium, suggesting that they share the same poetic training and background.Classic
Essays in Environmental Economics and Public Health
Get PDFThis dissertation comprises three essays focused intersection of environmental economics and public health, each examining a consequence of wildfire smoke exposure.
The first chapter investigates the causal impact of short-term smoke exposure on hospital care utilization in Oregon. Using daily ZIP code-level panel fixed effects models (2008-2022), I show that wildfire smoke significantly increases both emergency department visits and inpatient admissions. I further estimate the cost savings under a counterfactual reduction of 2020-2022 smoke levels to those in 2008-2010, finding that avoided inpatient stays account for 80 percent of total healthcare savings.
The second chapter examines behavioral responses to fine particulate pollution (PM2.5) and wildfire smoke across three domains: information seeking, recreation, and mobility. Leveraging weekly Google Trends at the DMA-level, monthly National Park visitation data, and daily traffic counts in Oregon, I find that increasing PM2.5 unexpectedly dampens search interest for most air-quality topics, heavier density smoke plumes reduce park visits especially in outdoor-focused parks, and smoke exposure reduces local travel volume.
The third and final chapter focuses on the impacts of smoke plumes on health by examining monthly mortality in U.S. counties from 2006 to 2019. Using CDC mortality data, I find an additional smoke day raises all-cause mortality rates (per 100,000), with larger effects at higher plume densities and among older adults. I also highlight the robustness of smoke to different configurations (smoke days, binned, continuous measures).Public Polic
Agitational Photography, 1930–1945: Lola Álvarez Bravo, Claude Cahun, Suzanne Malherbe, and John Heartfield
No full textThis dissertation explores how photography was put to work between 1930 and 1945 to agitate against fascism, imperialism, and capitalism. It investigates the material and technical aspects of how John Heartfield (b. Germany, 1891–1968), Lola Álvarez Bravo (b. Mexico, 1903–1993), and the partnership of Claude Cahun (b. France, 1894–1954) and Suzanne Malherbe (b. France, 1892–1972) used photographs to transmit their radical leftist politics. Each chapter examines how a particular body of their work was made. Chapter One discusses Heartfield’s photomontages as photomechanical prints. His creative interventions in the processes of rotogravure and halftone produced montages that critiqued the Nazis, trained viewers to understand photographic manipulation in print media, and encouraged audiences to take up montage and put it to work for the transnational anti-fascist movement. Chapter Two offers the first anti-colonial reading of Cahun and Malherbe’s photographic work. Sharing their Kodak and using commercial photo shops, they made snapshots that critiqued imperial practices of display in Paris and London as they circulated in surrealist and anti-colonial networks. Chapter Three explores Álvarez Bravo’s photographic labor both in her journeys across Mexico and in her domestic spaces. From her kitchen darkroom, Álvarez Bravo anticipated the circulation of her work in print as she created photographs and photomontages that honored the often-overlooked work of sewing, cleaning, and teaching, archived leftist protests, and motivated Mexicans to resist capitalism and fascism.History of Art and Architectur
Measurement in K-12 Policy Analysis
Get PDFThis dissertation consists of three papers that consider the construction, role, and use of educational measures in educational policies and evaluation methods. Educational measures, such as student test scores, are widely used to evaluate the effectiveness of educational programs or policies.
The first paper investigates the properties of school quality scores in state educational accountability systems under the Every Student Succeeds Act (2015). I use multilevel modeling and factor analysis to simulate an accountability system based on a state’s existing student- and school-level data. I find that this system exhibits high classification accuracy of the state’s lowest performing schools, particularly for elementary schools. I also test how classification accuracy varies due to common policy decisions and show that these design choices have differential effects by school level. This challenges uniform accountability approaches across school levels and suggest the need for level-specific policy decisions in designing these complex systems.
The second paper explores the use of a nonparametric surface response estimation method, Gaussian process regression (GPR), in educational two-dimensional regression discontinuity designs. Regression discontinuity designs are used to estimate the effectiveness of policies or programs, which in education are commonly provided to students based on their scores on multiple tests, such as math and reading. GPR allows one to target an estimand of a boundary average treatment effect as well as understand treatment effect heterogeneity in student outcomes. In simulation, GPR exhibits stronger statistical properties compared to existing methods, and it improves the analysis of an empirical example of a state’s English Language Learner reclassification policy based on two test scores.
The third paper analyzes how state policy documents discuss the use of student sociodemographic variables in constructing teacher value-added model (VAM) scores. VAMs are used to evaluate educators through comparisons between expected and observed student test scores, conditioning on students’ prior achievement and other information. Despite states’ agreement that the role of student background in academic performance should be statistically accounted for when evaluating teachers to increase fairness to educators, I find that states work against their stated goals by tending to exclude race from these calculations, which I examine using tenets of quantitative critical theory.Educatio