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Adaptation and Mitigation Measures and their Policymaking Processes in Shiga
No full textShiga Prefecture’s climate change policy stands out for two key reasons: (1) it employs backcasting, supported by a quantitative model, to design its mitigation strategies; and (2) it was one of the first regions in Japan to initiate adaptation efforts, including detailed impact assessments funded by national subsidies. A critical factor in this policy process is the involvement of the local environmental research institute. This institute serves as a vital bridge between the scientific community and local government, playing a central role in developing both mitigation and adaptation plans by incorporating scientific projections and knowledge
When and Where I Enter: A Stakeholder Analysis of Why Centering Black Women in Legislative Leadership and Policy is the Blueprint for Achieving Health Equity and Preventing Cancer and Other Chronic Diseases
No full textThis research study explored the relationship between racialized gender identity and legislative sponsorship of policies that address the social determinants of health and center Black women in policy. A purposive sample of Black and non-Black United States legislators serving at the local, state, and federal levels between 2015 and 2025 was utilized for stakeholder and policy analyses.
The findings of this research study indicated that Black U.S. Congresswomen (N=37) have sponsored more legislation relating to the five social determinant of health domains in comparison to non-Black U.S. Congresswomen (N=180). Moreover, the results showed that policies that center Black women are disproportionately sponsored by Black women legislators (N=39) and most prevalent in the Southern region of the United States (N=29). In 2024, the majority of Black women elected to public office at the local, state, and federal levels identified as members of the Democratic party (74%) and won as Incumbents (N=355). Furthermore, current opportunities for Black women to enter public office in 2025 are most frequent at the local level of U.S. government
Youth Reclaiming Environmental Narratives and Identities through Postcolonial Intersectional Environmentalist Digital Activism for Environmental Justice
No full textThrough critical autoethnography, bricolage, and action research approaches, this qualitative study examined how high school students engaged in/with environmental justice through digital activism while reflecting on their personal identities and environmental science education.
This novel research created space to nurture the interrelationships among intersectionality, youth climate action, environmental justice (EJ), science education, and digital activism. Furthermore, it included the researcher’s autoethnography to share her process of reclaiming her identities and narratives. The data was analyzed using postcolonial and intersectional environmentalist frameworks.
During ten sessions of virtual after-school meetings, the participants learned about the 17 principles of EJ and intersectional environmentalism. We examined colonial narratives in environmental science, with a particular focus on BIPOC communities.
Furthermore, the intersectional environmentalist framework enabled us to critique how diverse identities were represented in environmental science and EJ digital activism. The purpose of this study was to support youth in creating an environmentally just society while deepening their scientific understanding and identity development. Furthermore, it provided teachers with insights on creating more inclusive and just science classrooms
“I wanted to be known by them”: Teachers’ Perceptions on Reflective Practice in Applied Keyboard Instruction
No full textThe literature on adult learning acknowledges reflection as essential and transformative in the process of learning. There are also recent studies demonstrating the value of reflective practice for the field of music education, with such benefits including awareness to one’s strengths and weaknesses, increased mindfulness and confidence, and effectively planning for future improvement. However, there is a dearth of research on the use of reflective practice in applied instruction – both teachers’ methods of reflection on their work, and the use of reflective practice for their students; and not enough is known on whether applied teachers perceive reflective practice as valuable.
This qualitative study examined applied keyboard teachers’ perceptions on reflective practice, whether they use it in their work and if so in which manner, and how the use of reflective practice affects the teacher-student relationship. Semi-structured interviews were conducted with four experienced keyboard instructors working in postsecondary institutions, and focus group sessions were held with their students. Data from the interviews and focus groups were transcribed, coded, and grouped into inductive themes, and thereafter underwent cross-case analysis.
The findings revealed that teachers’ perceptions of reflective practice, their use of it, and its effect on the teacher-student relationship, are inextricably connected. All teachers reported using reflective methods with students, and most believed in the necessity of self-reflection on their own teaching. Additionally, most teachers were not trained in the use of reflective practice and were not sure how it is defined in applied instruction; having learned it from observing their own teachers, each used it differently, according to their personality and teaching philosophy, and based on their students’ idiosyncratic learning needs. In addition, the balance between the master-apprentice and learner-centered approach in different teachers’ work emerged as influencing their use of reflective practice.
Interview and focus group participants viewed reflective practice as beneficial and highly advantageous, and as having a positive effect on the teacher-student relationship. Several challenging attributes of reflective practice were also described, such as reflection as excessive, time consuming, causing discomfort and provoking self-criticism.
The study provides a definition of reflective practice for the field of applied instruction, and shows its value for teachers and students alike, alongside the necessity of providing training to assist instructors in using reflective practice effectively, while addressing any potential shortcomings
Validity of Automatic Speech Recognition for Intelligibility Assessment in Children with Dysarthria
No full textPurpose: Accurate assessment of speech intelligibility is critical for children with dysarthria secondary to cerebral palsy (CP). Traditional human assessment, such as orthographic transcription and perceptual ratings (e.g., ease of understanding; EoU) can be highly time-consuming or subjective in clinical practice and research. Automatic speech recognition (ASR) may provide a more efficient, objective alternative, but its validity for intelligibility assessment in this population remains unexamined.
This study evaluated the validity of ASR as a tool for intelligibility assessment in children with dysarthria. The most suitable ASR systems for approximating human intelligibility assessment were identified. Methods: Five ASR systems transcribed speech samples produced by twenty children with dysarthria. Additionally, 168 adult listeners provided orthographic transcriptions and EoU ratings of the samples. Word recognition rate (WRR) was measured for both ASR and human listener transcriptions. Pearson correlations were used to assess the relationship between ASR-generated WRR and human WRR, as well as between ASR-generated WRR and human EoU ratings.
Results: Four ASR systems (WhisperX-small, WhisperX-medium, WhisperX-large, and Google Cloud) showed strong correlations with human WRR, with WhisperX-medium demonstrating the strongest correlation. The four systems also exhibited strong correlations with EoU ratings, with Google Cloud ASR showing the strongest correlation. In contrast, Wav2Vec2 demonstrated a weak correlation with both human WRR and EoU ratings.
Conclusions: ASR shows promise as an adjunct tool for intelligibility assessment in children with dysarthria. If developed further, ASR could also be used for real-time feedback on intelligibility to help the children practice their speech skills independently. Of the ASR systems tested, WhisperX-medium appears most promising for approximating human transcription accuracy, whereas Google Cloud ASR is best suited for approximating perceptual ratings. However, differences in ASR performance highlight the need for careful system selection for appropriate clinical applications in this population
Ability of diastolic arterial pressure to better characterize the severity of septic shock when adjusted for heart rate and norepinephrine dose
No full textBackground
Septic shock is commonly associated with reduction in vasomotor tone, mainly due to vascular hyporesponsiveness to norepinephrine (NE). Although the diastolic arterial pressure (DAP)/heart rate (HR) ratio reflects vasomotor tone, it cannot be a reliable index of vascular responsiveness to NE (VNERi). We hypothesized that adjusting DAP/HR for the NE dose could yield a VNERi value (VNERi = DAP/(NE dose x HR)), knowledge of which can help guiding therapeutic strategies in cases of persistent hypotension despite NE (e.g., increasing NE doses vs. introducing additional vasopressors). For our hypothesis be valid, at least VNERi should demonstrate a stronger association with patient outcome than DAP, DAP/HR or mean arterial pressure (MAP)/NE dose, a global marker of NE responsiveness.
Methods
We conducted a post-hoc analysis of the ANDROMEDA-SHOCK database. Hemodynamic variables and initial NE doses were recorded at the randomization time-point, within 4 h of septic shock diagnosis. NE doses were expressed in µg/kg/min (using the bitartrate NE formulation). A multivariate model was employed to compare the associations between these variables and key clinical outcomes, including in-hospital mortality, numbers of vasopressor-free days and of renal replacement therapy (RRT)-free days up to day 28.
Results
The ANDROMEDA-SHOCK database included 424 patients with septic shock receiving NE. The median DAP was 52 mmHg [IQR: 45–50] and the median NE dose at inclusion was 0.2 µg/kg/min [IQR: 01-0.4]. In-hospital mortality was 43%. VNERi demonstrated the strongest association with in-hospital mortality compared to DAP, DAP/HR, and MAP/NE dose, emerging as the most significant covariate in the multivariate model. Similar findings were found for the associations with numbers of vasopressor-free days and RRT-free days up to day 28. The model revealed an inverted J-shaped relationship between in-hospital mortality and VNERi, with a nadir point at 6.7, below which mortality increased.
Conclusions
In patients receiving NE during early septic shock, VNERi demonstrated the strongest association with outcome compared to DAP, DAP/HR, and MAP/NE dose. Due to its physiological basis and robust association with outcomes, VNERi may serve as a valuable bedside marker of the vascular responsiveness to NE. This index could potentially be integrated into decision-making of early septic shock
A Turning Point? How NYC’s 2025 Mayoral Election Could Redefine Climate Justice and Inequality
No full textNew York City’s 2025 mayoral election represents a pivotal juncture at which decades of uneven climate action, racialized austerity, and infrastructural neglect could either be entrenched or reoriented toward a more redistributive model of urban governance. This paper argues that the election will function as a stress test for whether climate policy in New York can move beyond technocratic resilience toward a justice-centered framework that materially redistributes resources, risks, and decision-making power to frontline neighborhoods long marginalized by zoning, policing, and disinvestment. Drawing on recent citywide debates over congestion pricing, public housing retrofits, flood resilience, and budget cuts to social services, the analysis situates the 2025 race within a broader struggle between “green growth” approaches aligned with real estate and finance interests and insurgent movements demanding decommodified housing, fare-free and decarbonized transit, and robust protections for low-wage, immigrant, and care workers. By tracing how candidates’ platforms, donor coalitions, and governing coalitions engage with these demands, the paper shows that the election could redefine the meaning of climate leadership in New York—from a narrow focus on emissions metrics to a thick conception of climate justice grounded in racial equity, labor rights, and democratic planning. Ultimately, the paper contends that the outcomes of this election will have implications that extend beyond city limits, offering a test case for how large, unequal global cities navigate the intertwined crises of climate change, affordability, and authoritarian backlash in the coming decade
The Econometrics of Matching with Transferable Utility: A Progress Report
No full textSince Choo and Siow (2006), a burgeoning literature has analyzed matching markets when utility is perfectly transferable and the joint surplus is separable. We take stock of recent methodogical developments in this area. Combining theoretical arguments and simulations, we show that the separable approach is reasonably robust to omitted variables and/or non-separabilities. We conclude with a caveat on data requirements and imbalanced datasets
Agriculture in a Changing Climate: Applications of Machine Learning and Remote Sensing for Measurement and Adaptation
Full text linkThis work considers how large-scale datasets and novel machine learning methods can be applied to challenges in climate and sustainability, with a particular focus on agriculture. Effectively leveraging these advancements for sustainable development research requires answering two questions: first, how can complex data be translated into useful and accurate information? And second, under what circumstances does this information offer real insight into an important problem? In answer to the second of these questions, the research in the three chapters of this dissertation falls broadly into one of two categories: problems for which high spatial- or temporal-resolution data is necessary but infeasible to collect at scale (Chapters 1 and 3); and problems for which the structure of relationships between features and outcomes is complex, with important non-linearities, interactions, or other nuances that may be overlooked by traditional approaches (Chapters 1 and 2).
Both such categories of problem are common in the domain of agriculture, an industry which is critical for food security and economic well-being, but highly susceptible to fluctuations in weather and climate. In Chapter 1, I introduce and validate a method for creating high-resolution estimates of planting and harvest dates for United States crops with satellite imagery. This data is an important input for many research applications, but is only tracked at the state level. The resulting dataset is then used to generate more accurate measures of the weather conditions crops are exposed to during their growing season, and thus more precise estimates of how these conditions impact yields. These estimates suggest a 17% larger impact of extreme heat (>29C) on crop yields than previously documented, with substantial variation in heat sensitivity over the course of the growing season. However, the overall impact of increased temperatures is partially offset by a reduced estimate of growing season duration and a 276% increase in the estimated benefits of warm (10-29C) temperatures. Finally, I present novel evidence that farmers use early planting as a form of adaptation to warming, with planting dates shifting earlier by 0.13 days for each additional 30C day during the growing season.
Chapter 2 presents an even more flexible formulation for estimating US crop yields. I introduce a deep learning model that predicts yields directly from daily weather data, and show that it reduces out-of-sample error by 10.7% relative to standard linear modeling approaches. Using interpretable machine learning techniques, I demonstrate that this model learns a number of nuanced patterns consistent with expectations from agronomic theory, including spatial and geographic variation, interactions between weather features, and nonlinearity over weather feature values. Over several simulations, these models estimate future impacts of warming that are two to three times less severe than prior modeling approaches would suggest. However, the complexities of causal identification with highly flexible models mean that these results must be interpreted with caution; primarily, they suggest that estimates of climate impacts may be highly sensitive to feature selection, and to precise trends in warming over the course of the growing season.
Finally, Chapter 3 turns to smallholder farms in Kenya, as part of research done with support from Atlas AI. A collection of approaches for real-time yield monitoring at the field level are introduced and tested, using satellite-based assessment of vegetation health. I discuss a remotely-sensed proxy for crop yields for use in environments where reliable ground truth data is unavailable, and present a model that can capture 73.5% of variation in this yield proxy by roughly 6 weeks post-planting. A range of approaches are evaluated for incorporating location- and crop-specific features, handling low volumes of training data, and adjusting for variable timing of satellite imagery collection.
Taken together, these chapters demonstrate the value of remote sensing and machine learning for understanding the impacts of climate on crops and identifying strategies for adaptation. They also emphasize the complementarity between novel machine learning approaches and traditional statistical and economic methods: in Chapter 1, for example, satellite imagery is used to generate a novel dataset for analysis with more standard models; and in Chapter 2, I present a non-parametric approach to feature discovery for future causal inference work. Finally, these chapters demonstrate that estimates of climate impacts can be highly sensitive to what features are used and how they are encoded; this underscores the importance of careful consideration in constructing accurate feature inputs, and caution in interpreting the results of any one model
Parthood without Mereology
No full textObjects have, and themselves are, parts. If we endorse a sufficiently liberal notion of object, anything is an object and anything, excluding the universe, is a part of some larger one. If we think that the universe, too, is an object, then any object is a part of it. What is it, then, for an object to be a part? Contra the orthodoxy, in my dissertation I argue that to be a part is no more a relation than to exist is a property. In fact, to be a part is just to be the value of a variable in the range of a quantifier whose interpretation has been extended. When I say that, for instance, my hand is a part of my body, I am not making the claim that two objects in the domain of quantification—my hand and my body—stand in a certain relation of ordering—being a part of—to one another. Rather, I am making the claim that the domain of quantification, which used to include my body but not my hand, has been expanded and now includes my hand. For the hand to be a part (of my body, but most importantly of the universe) is for it to exist in an expansion of the quantification domain.
As I construe it, the operation of re-interpreting the quantifiers—and, so, of individuating parts of objects—is both modal (the interpretations of the quantifiers are indefinitely extensible) and actuality-bound (the modality at play operates across interpretations, rather than across possible worlds). In the resulting ontology, the universe itself (i.e. effectively, the actual world) is the only object that exists before we start individuating its parts—that is to say, before we start expanding our domain. As such, individuating parts is an operation that is generative (with each re-interpretation, the domain includes new objects, which replace the previous ones, and its cardinality is higher than that of the domains associated with previous, less extended interpretations); maximally general (any new object is a part); and world-bound (every new object is a part of the universe). Insofar as it is indefinitely extensible, the interpretation of our quantifiers can always be extended, but does not need to be. Insofar as individuating the parts of any object is expanding the domain of quantification, the universe, which is the only object that exists in the non-expanded domain, is itself part-less, albeit extended. Similarly, the objects existing at further levels of expansions are, too, themselves part-less, for individuating their parts is, once again, expanding the domain. Mereological complexity is, strictly speaking, quantificational complexity.
The dissertation is written as three papers. In the first paper, “Composition as Analysis: The Meta-Ontological Origins and Future of Composition as Identity” I argue that a non-trivial formulation of the claim that a composite object is the same as its parts requires that we construe parthood quantificationally. I then suggest that we construe the system of domain expansions as an information ordering and interpret the corresponding many-one identity statements as metaphysically informative. In the second paper, “Parthood Without Mereology,” I present an antinomic result for parthood: that we cannot both construe coincident objects as numerically distinct and mereologically indiscernible while also claiming that absolutely every object coincides with at least one other object. I blame a relational account of parthood for this result and argue that switching to a quantificational account is needed both to make sense of the problem and to find a solution. In the third and last paper, “To be said of as a quantifier: quantity, parts, and the invention of ontology in Aristotle’s Categories,” I take on an interpretive challenge from Aristotle’s Categories and show that the challenge could be met by appreciating that Aristotle has a non-relational notion of parthood and re-thinking his account of quantity on that basis