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A Market for Vice: An Exploration of Strategic Irresponsibility
No full textOrganizational scholarship has assumed that corporate irresponsibility (CI) is largely detrimental to corporate financial performance. Alternatively, CI may sometimes work in firms' favor, though at the expense of stakeholders. Exploring this reality, I argue that many firms engage in strategic CI because there are short-term financial benefits or at least no clear financial payoffs for behaving otherwise. I critique the literature on CI and conceptualize the construct as more then corporate illegality and distinct from both corporate policy and low CSR. I then explain the proliferation of strategic CI as a strategy that firms employ toward competitive advantage. Importantly, CI becomes strategic when it is persistent and pervasive. Strategic CI can also be identified by a firm's use of public-facing CSR as a decoupling mechanism to buffer against and to obscure their CI as well as by increased corporate political activity as a sign of firm efforts to legitimate a firm's concurrent CI
Practice Variation as Mechanism for Generating Institutional Complexity: Local Experiments in Funding Social Impact Business
No full textInstitutional complexity shape what is perceived as possible in organizations by framing cultural debates about practices, but organizations in turn shape how logics interpenetrate fields, suggesting that we must consider in tandem the degree of compatibility between logics and the degree of practice variation in a field. We offer a recursive view that considers how multiple institutional logics shape practices and how organizations select, adapt and create new practices that in turn influence the institutional complexity of a field. Our study of three entrepreneurial impact finance organizations in the Seattle area considers how they situate their practices vis-à-vis the market and community logics, balancing the tensions of money and value, maximization and sufficiency, self- and common-interest, and global and local focus. Rather than framing these tensions as simply conflicting, we note differing degrees of logic compatibility ranging from aligned to incompatible. Our study indicates that when organizations adapt and invent practices, they decrease the specificity of means/ends relationships within the field, broaden the scope of the dominant market logic, and create openings for additional innovation. This shift in the field toward greater plurality of logics occurred as the result of uncoordinated, routine activity by entrepreneurial organizations rather than through the coordinated efforts of powerful actors
Black Children Matter
No full textMaster of Social Work (MSW)Racial disproportionality is defined as a condition that exists when the proportion of one group in the child welfare population is proportionately larger (overrepresented) or smaller (underrepresented) than the proportion of the same group in the general child population (Detlaff & Boyd, 2020). Being Black is part of my identity and something I take pride in. It is no secret that historically Black people have experienced disproportionality, assimilation, and racism. As I have grown through my social work journey, I have realized my passion is children and preparing them to lead the future generations. All children deserve the right to safety, well-being, and permanency. Throughout history, racism against Black people has been prevalent at every level. In child welfare, Black children are disproportionately represented
Wolfed: The Sociopolitical Implications of being Animalized in the Middle Ages
No full textThesis (Ph.D.)--University of Washington, 2025In this dissertation, the primary point of interest is the wolf’s voice and its portrayal of agency in German medieval literature and reception thereof. For this reason, examples in which the wolf itself speaks, or acts to address its own sociopolitical status, and comments on issues of being an outsider, or having been made an outsider, are of particular interest.I analyze various medieval texts that portray realistic as well as allegorical wolves. These texts include receptive works by German Romanticists who engage with medieval material and culture specifically connected to the wolf motif. Within this analysis, I show the cultural value of the wolf motif in literature, and, due to the motif’s ambivalent and ambiguous implications in Western thought, I focus on the wolf’s sociopolitical status as an outsider and its liminal nature in relation to society and humanity.
In analyzing the literary wolf in medieval German literature, I focus on the ambiguous implications of what it means for a character to be given wolfish characteristics, or to be made a wolf. This process of wolfing interplays with attitudes toward the animal and its cultural value. I claim that wolves have, on the one hand, been given a predominantly negative stigma. Like the real animal that was free to be hunted and killed in medieval times, allegorical wolves are individuals associated with the wolf motif as an intrinsically negative, and socio-politically hostile characteristic in literature. For individuals to have been wolfed means, concretely, that the animal and the human individual are in some form silenced, exiled, prosecuted, and similarly ostracized. The concept of being made a wolf is complex because, the wolf and wolfed individual hold, on the other hand, highly desirable qualities such as strength, bravery, and independence in their wolfed status. I argue that these wolfed individuals frequently use their abilities and skills to both survive and to stand up against the specific sociopolitical grievance that the repressive social structure used to make these individuals into wolves in the first place. Being wolfed, in other words, includes positive connotations like survival strategies in a hostile environment, such as a repressive society. Acknowledging both sides of the wolfish qualities underscores the relevance of wolfish voices and their role in formulating a more just sociopolitical constellation by calling out injustices in the first place.
This study shows the importance of acknowledging the ambivalence of the wolf motif to create a more tolerant society. The function of the wolf motif in literature is a signal toward sociopolitical grievances, and how these grievances reflect prejudices and biases. Of course, the wolf is not only innocent and misunderstood, but also a dangerous predator. However, with regard to individual freedom to participate and formulate social structures and regulating its rules for a thriving environment, all voices need to be taken into account, and the wolf’s voice is significantly strong
Examining Ocean Mixing Dynamics at the Namonuito Guyot and Nam 2. Atoll
No full textThis study investigates the impact of guyots and atolls on ocean currents and mixing
processes in the Caroline Islands, Micronesia. The hypothesis is that atolls enhance vertical and
horizontal mixing more effectively than guyots due to their surface-reaching morphology. To test
this hypothesis, vertical profiling was conducted using underway CTD (Conductivity,
Temperature, and Depth) and ADCP (Acoustic Doppler Current Profiler), along with
calculations of mixed layer depth, stratification, mixing rate measurements, and Thorpe scale at
Namonuito Guyot and an unnamed atoll near the guyot, referred to as Nam. 2 Atoll in this study.
The findings reveal significant differences in mixing dynamics between the two features. The
atoll exhibited stronger mixing and a more uniform mixed layer, driven by its interaction with
surface currents and waves. In contrast, the guyot showed more stratified layers and weaker
mixing, reflecting its submerged nature and limited interaction with surface processes. These
results provide insights into the physical processes governing these geological features and their
influence on ocean circulation, highlighting the distinct roles of guyots and atolls in shaping
ocean mixing dynamics
Flow as a Mediator of Ecosystem Engineering: Hydrodynamics Shape Chemical Modification by Kelp and Mussel Beds
No full textThesis (Ph.D.)--University of Washington, 2025Ecosystem engineers are organisms that modify their physical and chemical surroundings in ways that shape the structure and function of ecological communities. Physically, they build biogenic structures that modify flow, light, and habitat complexity. Chemically, they change oxygen and pH levels through metabolic processes such as photosynthesis and respiration. These modifications can either facilitate the presence of associated species by creating favorable microhabitats or inhibit them by amplifying environmental stress. Understanding the circumstances under which and how these shifts occur has become increasingly important as climate change intensifies environmental variability in coastal ecosystems. Advancing our understanding of how ecosystem engineers shape their communities requires considering how external factors, particularly flow, mediate their influence on the surrounding environment. Driven by tides, waves, and currents, flow regulates water residence time and thus the accumulation or dispersion of biologically modified water. Yet despite its central importance, the role of flow in controlling the strength and direction of ecosystem engineering remains poorly understood.This dissertation examines how local hydrodynamics influences the capacity of marine ecosystem engineers to modify their surrounding chemical environments. It focuses on two contrasting but complementary systems: an autotroph, bull kelp (Nereocystis luetkeana), and a heterotroph, mussels (Mytilus spp.). Looking across these systems provides a broader view of how different types of engineers—those that produce oxygen through photosynthesis and those that consume it through respiration—shape their local chemical environments. By studying both systems, this work links two aspects of ecosystem engineering: 1) oxygen production and depletion, and 2) explores how flow determines when these species have the potential to act as facilitators or inhibitors within their communities. I combined field observations with laboratory and field experiments to explore how flow dynamics interact with biological traits, such as canopy structure, density, and behavior, to determine when these engineers act as facilitators or inhibitors within their communities. Across chapters, the work progresses from identifying environmental controls on kelp-driven chemical modification (Chapter 1) to isolating mechanistic feedbacks between flow, mussel behavior, and chemistry (Chapter 2), and then investigating density effects on chemistry and behavior by out-planting manipulated mussel aggregations in natural conditions (Chapter 3).
Chapter 1 addresses a fundamental gap in understanding how hydrodynamic variability constrains the ability of kelp forests to alter seawater chemistry. Using high-frequency, long-term measurements of flow, light, dissolved oxygen (DO), and pH, this chapter quantifies how diel and tidal cycles interact to control the timing, magnitude, and spatial pattern of kelp-driven chemical change within a tidally dominated bull kelp forest in the Salish Sea. The results show that kelp effects on local seawater chemistry are not static “hotspots” but dynamic, flow-dependent features that shift predictably across space and time. Kelp-driven increases in DO occur primarily during daytime slack tides, when reduced flow allows oxygen-enriched water to remain within the canopy before being rapidly replaced by the next tidal exchange. These findings demonstrate that even in a highly productive kelp forest, strong and variable tidal currents limit the persistence of chemical modification to only a few hours per tidal cycle. As a result, the capacity for kelp forests to function as chemical refugia depends less on their metabolic potential and more on the hydrodynamic context that influences water retention and exchange. By explicitly linking diel and tidal processes, this chapter reframes kelp-driven buffering from a static to a dynamic process and provides a framework for predicting when and where macrophyte canopies can locally ameliorate chemical stress.
Chapter 2 builds on this framework by examining how flow and organismal behavior mediate chemical modification in a heterotrophic engineer, the mussel. Valve gaping in mussels regulates the flow generated by their pumping activity, which drives water exchange between the ambient environment and the interstitial spaces within aggregations. This chapter presents an experimental approach that couples behavioral measurements from high-frequency gape sensors with real-time oxygen data to evaluate how valve activity and flow together shape interstitial water chemistry across three Mytilus species. Two consistent patterns emerged: oxygen depletion within mussel beds decreased exponentially with increasing flow speed, and gaping behavior remained largely static across flow and low-oxygen conditions. The absence of compensatory gaping under low-flow conditions indicates limited behavioral feedbacks between gaping, chemistry, and flow, underscoring the dominant role of physical flow in driving oxygen dynamics within mussel aggregations. Variation in oxygen depletion among species was best explained by differences in biomass density, suggesting that morphometric traits, rather than behavior, primarily govern their capacity for chemical modification. These findings refine our understanding of ecosystem engineering by identifying the conditions under which structural and hydrodynamic factors outweigh behavioral influences.
Chapter 3 builds on insights from Chapter 2 by extending the work into the field, where mussel aggregations experience natural tidal flow and greater variation in density. The first goal was to determine whether higher mussel densities lead to stronger oxygen depletion under natural flow conditions. A second goal was to test whether the relationship between flow speed and dissolved oxygen follows the same exponential pattern observed in the steady-flow flume (Chapter 2), and whether mussel gaping remains insensitive to flow and oxygen variation across different aggregation positions in a more dynamic environment. The field experiment showed that oxygen concentrations declined sharply with increasing aggregation density, with the highest-density aggregations exhibiting the lowest mean DO levels, the largest diel fluctuations, and frequent short-lived hypoxic events. Gaping behavior varied with density and position within an aggregation, as interior mussels gaped wider and spent more time open than edge mussels, but showed little response to short-term changes in flow or oxygen availability. These results demonstrate that structural traits of an aggregation, such as density, amplify chemical modification, while flow regulates its magnitude and persistence. Moreover, there was no evidence that behavior provides any buffering capacity once physical exchange is constrained.
Across systems, this dissertation highlights a unifying principle: the capacity of marine engineers to alter their environment depends primarily on how their biological traits, such as metabolism, structure, and abundance, interact with hydrodynamic forces. By quantifying how flow controls oxygen variability across autotrophic and heterotrophic systems, this work advances a better understanding of when and where ecosystem engineers function as facilitators or inhibitors, emphasizing the central role of local physical dynamics in shaping their ecological influence
Mechanistic Modeling of Degrading Perovskite Solar Cells – Investigating Device-Level Degradation Phenomena and Informing Predictive Machine Learning Models of Operational Lifetime
No full textThesis (Master's)--University of Washington, 2025Halide perovskite (HP) photovoltaics (PV) are a high-performance, low-cost alternative to traditional crystalline silicon (c-Si) PV, but their short operational lifetimes prevent them from reaching commercial scale. Alongside other processes, HPs chemically degrade under elevated temperature, oxygen, moisture, illumination, and electrical bias, and this chemical decomposition is the primary driver of HP PV performance decline. In previous studies, we proposed mechanisms and developed kinetic rate law models for the chemical decomposition of three relevant HP materials, and we developed predictive machine learning (ML) models for the optoelectronic properties of these HP films and for device operational lifetimes. Although, no mechanistic models of device performance decline exist. Additionally, our initial predictive models of operational lifetimes require our kinetic rate law models to be accurate, and these models are both composition-specific and time-intensive to develop. In this work, we fill these essential gaps by mechanistically modeling degrading perovskite solar cells (PSCs) and improving our predictive ML models for their operational lifetimes. Specifically, we globally fit the non-ideal diode model and a custom, one-dimensional (1D) drift-diffusion model to light and dark current-voltage (J-V) scans over time for devices degrading under varying temperatures, oxygen concentrations, humidities, and illumination intensities. Moreover, we quantify effective fractional active areas and thicknesses of HP films over degradation from in situ dark-field (DF) microscopy measurements, constituting an effective model of degradation profile over degradation. The extracted diode and drift-diffusion fitting parameters and their corresponding derived parameters are mechanistic properties of the device, and coupled with these effective degradation profile parameters, the evolutions of and correlations among these parameters over degradation illuminate the mechanisms of device performance decline. Furthermore, in a unique cumulative sensitivity analysis (CSA), we calculate the exact influence of each fitting parameter on each solar cell parameter over time, quantifying the exact influence of each degradation mechanism on device performance decline. Last, we analyze the relationships between parameter evolutions and degradation conditions including Arrhenius modeling to inform the development of both accelerated aging models and long-lived device design in future work. Overall, these analyses constitute the most advanced mechanistic model of PSC performance decline to date. Then, beyond mechanistic modeling, we utilize these various parameter sets as features in predictive machine learning (ML) models of operational lifetimes (T80), achieving a champion model applicable to all three of our PSC architectures with a mean-normalized root-mean-squared (RMS) error (NRMSE) of 26.5% using features derived only from temperature and the first 20 J-V measurements, without requiring the other degradation conditions or the composition-specific kinetic rate law models necessary for our previous predictive ML model. The predictive ML models developed in this study are the strongest we have produced in both accuracy and applicability, and we thus demonstrate the ability to use empirical and modeling parameters as features to construct predictive ML models for the operational lifetimes of multiple PSC architectures from small device degradation datasets using common, low-cost electronic measurements (e.g., J-V scans). This establishes a strong foundation for and represents a powerful step toward high-throughput device testing and thus long-lived device development
Design and Radiometric Modeling of a Portable EEM Fluorescence Sensor for ppb-Level Detection of Pesticide Mixtures in Water
Get PDFThesis (Master's)--University of Washington, 2025According to the U.S. Geological Survey (USGS), pesticide contamination of American waters is widespread, with typical samples containing mixtures of 10 to 20 active compounds. Recent studies show that agricultural runoff and seasonal application patterns are two of the most common sources of this contamination. Environmental monitoring studies help improve understanding of the distribution and persistence of pesticides in natural water systems. Enhanced detection tools are critical for environmental monitoring studies that target data collection and the analysis of water quality data. Traditional pesticide measurement methods include solvent extraction and chromatographic separation, which introduce problems such as: 1) high cost per sample, 2) slow turnaround time, and 3) limited suitability for field deployment. Recent advancements in fluorescence spectroscopy have allowed for the development of various portable measurement techniques in different applications. However, environmental agencies are still using laboratory-based analysis rather than portable optical measurement tools, which demonstrates that there is significant room for improvement in this field. The detection of pesticides using excitation-emission matrix (EEM) fluorescence requires accurate photon throughput calculation using component-based or radiometric modeling techniques. This thesis is a study of the design, modeling, and validation of an EEM fluorescence system based on multi-wavelength excitation theory. The system was designed, modeled, and evaluated in pesticide detection applications using three representative compounds: zeta-cypermethrin, myclobutanil, and glyphosate. The compounds were tested at five concentration levels to characterize the system across different detection scenarios. When compared to model predictions, the experimental results showed detection limits of 10-100 ppb for strongly fluorescent pesticides, approximately one order of magnitude above predicted values due to lower LED power than modeled. Based on the results and validation from the radiometric model, the use of compact EEM fluorescence systems in portable applications has potential to improve the frequency and cost-effectiveness of pesticide screening
Estimating HIV Cross-sectional Incidence Using Recency Tests from a Non-representative Sample
No full textThesis (Master's)--University of Washington, 2025Cross-sectional incidence estimation based on recency testing is an important tool in HIV research. This method has been used to estimate “placebo” incidence in active-control HIV prevention trials by applying the cross-sectional estimator to data from the screening population. The application of this approach faces challenges due to non-representative sampling, as individuals aware of their HIV-positive status may be less likely to participate in screening for an HIV prevention trial. To address this, a recent phase 3 trial introduced an test-based exclusion criterion: individuals were excluded during trial screening if they had recently taken an HIV test. To the best of our knowledge, the theoretical and empirical validity of applying a test-based exclusion criterion has yet to be studied. We develop a statistical framework that incorporates non-representative sampling and a testing-based exclusion criterion. We introduce a metric called the effective mean duration of recent infection that mathematically quantifies bias in the recency-based estimate of incidence. We investigate the performance of cross-sectional HIV incidence estimation in settings emulating current trial designs in an extensive simulation study. We find that when HIV negative individuals disproportionately attend screening for prevention trials, the traditional incidence estimator is unreliable unless all individuals with recent HIV tests are excluded from the sample. Additionally, we highlight a trade-off between bias and variability: excluding more individuals reduces bias from non-representative sampling but in many cases increases the variability of incidence estimates (even for a fixed sample size). Our findings emphasize the need for caution when applying the testing-based exclusion criterion and the importance of refining incidence estimation methods to improve the design and analysis of future HIV prevention trials
Computational and Rational Stabilization of Toll-Like Receptors for the Development of Novel Tools
No full textThesis (Ph.D.)--University of Washington, 2025Toll-like receptors (TLRs) are membrane-bound pattern recognition receptors essential for innate immune sensing, but their large, glycosylated extracellular domains and intrinsic instability make them notoriously difficult to express and purify recombinantly. These challenges have historically limited structural and functional studies, as well as the development of therapeutic reagents targeting TLRs. This dissertation presents a computational design framework for stabilizing and functionally interrogating TLRs, enabling the development of synthetic immunomodulatory tools. Using AI-guided design with ProteinMPNN, AlphaFold2 and RosettaFold Diffusion in addition to physics and rational approaches, we generated stabilized and expressible variants of TLR2 and TLR5, facilitating downstream applications including de novo minibinder generation and antibody development. Overall, this work highlights a generalizable approach to stabilizing immune receptors and advancing rational immunotherapy design