19614 research outputs found
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Entitlements, block grants, work requirements, and the safety net: Evidence from the US in times of economic crisis
No full textMarianne Bitler received her PhD in economics from MIT in 1998. She is currently a professor of economics at UC Davis, and has also worked at UC Irvine, RAND, and the Federal Reserve Board. Her research focuses on the effects of the means tested safety net and economics of the family. She is a co-editor of the Journal of Human Resources. She has served on a number of National Academy of Sciences, Engineering, and Medicine panels on topics related to social programs. She is a research associate of the NBER and a Research Fellow at IZA. Her research has been funded by NICHD, RWJ, and USDA. Professor Bitler's research focuses on the effects of government safety net programs on disadvantaged groups, economic demography, health economics, public economics, and the economics of education
Dominant hormone protocol: Directed life and the biopolitics of chemical messages
No full textIn 1905, Ernest Starling introduced hormones as “chemical messengers” to physicians at the University College London. In his lectures, Starling claimed that hormones “coordinate” the functions of the organs and that the discovery of hormones would allow physicians “absolute control” of the human body. As his paradigm treats hormones as bioinformation in a communications system where hormones are signalled and directed through the body toward target cells, I argue that hormones have emerged as a technology of biopower in scientific and medical practices.
Engaging in intersectional theories of biopower, my dissertation bridges conversations across Feminist Science and Technology Studies, Communication and Media Studies, and Cultural Studies to address how various industries’ representations, organizations, and directed flows of hormones produce and manage neoliberal subjects globally. This hormonal management is most starkly felt by those who resist or find alternatives to its many forms, including medical standardizations of gender affirming care, reproductive management, and hormonal pollution. I turn to scholarship across feminist science and technologies studies by Donna Haraway and Michelle Murphy, and to micha cárdenas’ work on algorithmic analysis in media studies, to think through the relations between hormones-as-information and directed life. Building on Alexander Galloway’s theorization of information protocol as biopower, I offer the term “dominant hormone protocol” to describe a system which directs hormones to and from certain subjects to manage those lives. Through this term, I show how hormones enact power differently across gendered, racialized, and species-distinct subjects. I turn to fictional and nonfictional stories of hormonal relations by Porpentine Charity Heartscape, Barbara Gowdy, and Drexciya as sites for rethinking protocol and countering the bioinformational model of Starling’s chemical messenger paradigm. Ultimately, I demonstrate how stories not only inscribe dominant hormone protocols but can also be speculative sites for imagining counterhegemonic alternatives to the flow of chemical messages.Graduate2025-06-202025-06-2
Infrared-Visible Image Fusion in the Gradient Domain
No full textDue to the complementary properties of the infrared cameras compared to conventional visible imaging cameras, it has become increasingly popular to fuse infrared and visible images of the same scene for better visual understanding.
One major application of this is surveillance which involves videos and requires fast processing. Therefore, there is a need for investigating novel low-complexity fusion algorithms that can be implemented in real-time applications.
In this study, we address this critical research problem by two-scale fusion in the gradient domain with saliency detection and image enhancement. In the proposed method, the source images are first decomposed in to base and detail layers.
Next, the base parts are fused in the gradient domain by choosing the maximum absolute gradient, whereas the gradients of the detail parts are fused using a weighted average where the weights are calculated using saliency maps.
Prior to fusion, the detail parts are enhanced using a guided filter-based enhancement approach. Finally, the fused gradients of the base and detail components are added together to obtain the gradients of the fused image, from which the fused image is reconstructed using a reconstruction technique based on wavelets. Experimental results demonstrate that the proposed method achieves very competitive performance in subjective and objective fusion assessments, while also outperforming most methods in terms of computational
complexity.Graduate2025-01-1
Racial disparities in cognitive functioning in middle and later life: The role of stressors as mediators and social resources as moderators
No full textThis dissertation explored the complex dynamics of racial disparities in cognitive functioning during middle and later life, examining the mediating role of stressors and the moderating influence of social resources within the Canadian context. Empirical analyses utilized baseline data from the ongoing Canadian Longitudinal Study on Aging, a survey of Canadians aged 45 to 85 years (n=51,338). Through ordinary least squares regression models, with survey weighting and multiple imputation for missing data, the study revealed the presence of racial disparities in cognitive functioning during middle and later life in Canada. Furthermore, using an intersectionality lens, the findings also revealed that race intersected with immigrant status and gender, influencing this health outcome as well. The application of the Stress Process Model (SPM) shed light on the mechanisms underlying these disparities. Both primary stressors (e.g., household income and homeownership) and secondary stressors (e.g., psychological stressors like self-rated general health, mental health, life satisfaction, and depression) mediated the relationship between race and cognitive test performance. Social resources such as marital status, social support and social participation demonstrated moderating effects on the relationship between specific stressors and cognitive functioning, and the moderation effect differs across races. Specifically, these social resources amplify the positive effects of some socioeconomic protective factors (i.e., reduced primary stressors) and subjective well-being factors (i.e., reduced secondary stressors/intrasychic strains) more for racial minorities than for whites.
These findings hold significant theoretical, research, and policy implications. A key theoretical implication of this study is the value of incorporating an intersectionality framework into the SPM for an understanding of how race interacts with other identities to affect cognitive functioning through differences in exposure to various stressors and social resources. There is also a need for research that compares different racial groups to understand variations in exposure to various stressors and their impact on cognitive health. Further, with regard to policy, our findings point to the need for policymakers to address racial disparities in socioeconomic status (SES) and intrapsychic or psychological strains in order to reduce racial disparities in cognitive health outcomes. Additionally, policymakers should focus on enhancing the social support networks of members of racial minority groups and increasing their social participation levels in order to alleviate the negative effects of stress-related exposures. Finally, future research should explore the persistence of racial inequalities in cognitive health outcomes in Canada, examining how socioeconomic factors and subjective psychological well-being contribute to these disparities over time, and compare different racial groups to understand variations in discrimination exposure and its impact on health.Graduate2025-08-2
Graduate experiences in community-engaged research: Exploring the motivations, barriers, and benefits of graduate students conducting community-engaged research
Get PDFIn recent decades, universities have increasingly emphasized collaboration between academic researchers and non-academic communities, leading to a growing use of community-engaged research (CEnR) approaches to address social and health-related issues. CEnR focuses on collaborative research between academic researchers and members of the community where the research topic or issue is situated – generally researching a topic that is put forward by the community in question. This trend has extended to graduate students, who are steadily adopting CEnR approaches in their theses and dissertations. However, limited research exists on the specific experiences of graduate students working within a CEnR framework, as well as on the factors that affect their capacity to meaningfully engage in this approach. This study explores the motivations, values, and experiences of nine graduate students conducting CEnR for their thesis or dissertation research. Through interviews, I examine how these students adopt CEnR practices, build relationships with community partners, and navigate the challenges unique to CEnR. Findings indicate that, beyond challenges commonly reported in the literature, graduate students face additional barriers, including limited knowledge and skills in CEnR, difficulties in establishing and sustaining community relationships, and the need to balance CEnR commitments with academic requirements and personal life. Participants suggested resources to support future CEnR students, including more undergraduate and graduate methods courses on CEnR, an accessible repository of CEnR materials, and additional funding for community engagement activities. Despite these challenges, graduate students value CEnR for its potential to create ethically sound, collaborative, and trust-based partnerships between academic researchers and community members.Graduate2025-12-1
How well do Earth system models reproduce the observed aerosol response to rapid emission reductions? A COVID- 19 case study
Get PDFThe spring 2020 COVID-19 lockdowns led to a rapid reduction in aerosol and aerosol precursor emissions. These emission reductions provide a unique opportunity for model evaluation and to assess the potential efficacy of future emission control measures. We investigate changes in observed regional aerosol optical depth (AOD) during the COVID-19 lockdowns and use these observed anomalies to evaluate Earth system model simulations forced with COVID-19-like reductions in aerosols and greenhouse gases. Most anthropogenic source regions do not exhibit statistically significant changes in satellite retrievals of total or dust-subtracted AOD, despite the dramatic economic and lifestyle changes associated with the pandemic. Of the regions considered, only India exhibits an AOD anomaly that exceeds internal variability. Earth system models reproduce the observed responses reasonably well over India but initially appear to overestimate the magnitude of response in East China and when averaging over the Northern Hemisphere (0–70∘ N) as a whole. We conduct a series of sensitivity tests to systematically assess the contributions of internal variability, model input uncertainty, and observational sampling to the aerosol signal, and we demonstrate that the discrepancies between observed and simulated AOD can be partially resolved through the use of an updated emission inventory. The discrepancies can also be explained in part by characteristics of the observational datasets. Overall our results suggest that current Earth system models have potential to accurately capture the effects of future emission reductions.This research has been supported by the Natural Sciences and Engineering Research Council of Canada (NSERC; grant nos. RGPIN-2019-204986 to Adam H. Monahan and RGPIN-2017-04043 to Nathan P. Gillett). Antonis Gkikas has been supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the 2nd Call for H.F.R.I. Research Projects to Support Post-Doctoral Researchers (project ATLANTAS; project no. 544).FacultyReviewe
Assessment and Detection of Landslide-Generated Tsunamis through Numerical Modelling and Instrumental Data
Get PDFThis PhD dissertation focuses on improving the understanding and mitigation of landslide-generated tsunamis in coastal British Columbia. With a history of landslide tsunamis, much of the coast is at risk of future damage. Here, I demonstrate the hazard of tsunami waves triggered by a large potential landslide in the Strait of Georgia, and develop a proof-of-concept methodology for the detection of landslides and triggered tsunami waves in the Douglas Channel region, using data from a network of seismic, hydroacoustic, and bottom pressure instruments.
The first study details numerical simulations of a potential large subaerial landslide on the coast of Orcas Island and resultant tsunami waves in the Strait of Georgia. Landslide motion and tsunami generation are modelled using the non-hydrostatic physics-based NHWAVE model. The simulated failure moves downslope at up to 13.6 m/s, traveling 732 m before coming to rest after 85 s. Tsunami propagation is continued using the fully nonlinear and dispersive Boussinesq wave model FUNWAVE-TVD in a succession of layered and nested grids. In the near-source region, modelled waves have peak amplitudes of 15-20 m, current speeds up to 10 m/s, and up to 30 m runup. Significant waves occur throughout the region surrounding Orcas Island. In the tsunami propagation direction, runup reaches 7.5 m at Neptune Beach near Lummi Bay. Both initial and reflected waves cause significant runup (> 1.5 m) along much of the shoreline between Point Roberts and Lummi Bay. The findings show that significant coastal impacts may result from landslide-generated waves in the region. Such waves would arrive with little or no warning, highlighting the need to improve tsunami hazard assessment and mitigation strategies.
The second study investigates the use of seismic, hydroacoustic, and hydrostatic pressure instrumental data, to determine an optimal method for landslide detection in the Douglas Channel region, with potential future application in a system to provide early warning of landslide-generated tsunami waves. A new landslide detection method was developed, integrating a Deep-Learning AI model known as EQT with the pre-existing SSNAP earthquake detection model to form the SSNAP-EQT model. Using waveform data from a network of 8 broadband seismic stations, the model was tested to determine if it could detect and locate a number of landslides documented in the region in 2017, 2022 and 2023. The results demonstrate the effectiveness of SSNAP-EQT in detecting landslides and even microseismic earthquakes. Limitations of the existing system include gaps in the station distribution and in data availability that affect the accuracy of event detection and location. Event detections were validated through the analysis of hydroacoustic data from a hydrophone near Kitimat. Analysis of hydroacoustic spectrograms shows great promise in enabling further characterization of landslide events. Data from a bottom pressure sensor near Kitamaat Village were used to demonstrate an effective method to detect and measure potential tsunami waves. An expanded network of hydrophones, pressure sensors, and seismic stations, strategically distributed across the study area, would significantly enhance the precision of landslide detection and enable effective early warning of triggered tsunami waves.Graduate2025-04-2
Vectors of Artificial Intelligence Ethics, Social Hope and Politics of Destiny
No full textI explore the idea that AI embeds itself in and (re)orders every aspect of human life by asking the question: What is the reality and the socio-political consequences of AI research and implementation? The dissertation is split into two main parts.
In part one, I interrogate AI discourses and trajectories to understand the magnitude of AI research and development. I begin with a cognitive AI research orientation as a means of positioning the methodological problems troubling AI research, innovation and implementation with a primary focus on the ethical limitations of AI creations. I follow cognitive AI methodology with computer scientist Ray Kurzweil’s critique of cognitive AI through his revelation of a neurological reality: a mind-based intelligence always already artificial in virtual simulation—brains simulate the mind. Finally, physicist and AI researcher Max Tegmark’s physics-based AI approach reveals the hopes and fears—ethical, social and political—associated with AI implementation as we move into the future—why the future is bright and exciting yet equally dark and dangerous.
In part two, I focus on questions unanswered by the vectored discourses in part one—an unrealized nonhuman metaphysics. First, we are pressed with the (de)positionality of humanity. Here, I place physicists turned social philosophers Karen Barad and Klaus Mainzer in exegetical discourse in order to understand nonhuman (yet fundamentally realist) orientations in a quantum-entangled universe. Doing so allows us to reposition human intelligence and anthropic wills toward knowledge as we move to understand the being of homo sapiens in an artificially intelligent Universe. Next, I turn our attention toward a history of intelligent orientations to break through the scientific obsession with advancement by asking how the orders of intelligence and artificiality have been patterned in the history of thought from the beginning of Western philosophy by focusing on the presokratics. Finally, I turn towards Indigenous science and knowledge creation (emphasizing myth) concerning quantum physics as a means of critiquing Western scientific understandings of intelligence. This turn towards Indigenous science expands on human hopes and fears of AI by interrogating the limitations of viewing AI problematics as future issues and instead seeing how future fears of dystopian orders exist today. By seeing dystopian realities today, we are better positioned to overcome both present and future failures of AI implementation in society.Graduat
Barriers and enablers to the adoption of buildings and energy efficiency initiatives in Greater Victoria
No full textKey messages:
- Focus group participants identify funding from provincial and federal governments as adequate and as enabling alongside staffing interactions.
- Staffing resources, the legislative, regulatory and political environment alongside governance and information and data management were identified as both barriers and enables.
- Political will and information exchange enable existing climate action, but municipalities lack of autonomy over the most effective policy instruments.FacultyUnreviewe
Canada’s Environmental & Social Due Diligence Legislative Landscape
No full textThis report examines the current environmental and social due diligence legislation landscape within the Canadian context and Canadian supply chains acting abroad. In recent years there has been a push from stakeholder groups, non-governmental organizations (NGO’s) and additional advocacy groups for stricter and mandatory environmental and human rights legislation and policy. This research finds that Canada has historically lagged in adopting and applying mandatory environmental and human rights compliance due diligence legislation for their supply chains in international contexts. Furthermore, this research illustrates that despite some progress, a significant gap in environmental and social due diligence legislation in Canadian supply chains continues to exist. Lastly, Bill S-211, and Bill C-262 illustrate Canada’s shift towards ensuring the protection of people and the environment within Canadian supply chains acting nationally and internationally.Jamie Cassels Undergraduate Research Awards (JCURA)UndergraduateReviewe