VictorJuiz/thesis huggingface dataset:
Fracturing White Feminism: Race, Nation, and Representation at the National Film Board’s New Initiatives in Film Program at Studio D
Keywords: Diversity Initiatives
Equity Studies
National Film Board of Canada
Studio D
White Feminism
Women's Movement

This dissertation examines the final years of Studio D, the state-funded, feminist film studio at the National Film Board of Canada (1974-1996) during its attempts to deal with the question of racial diversity within a post-multicultural policy Canada. As a national, feminist space, Studio D positioned itself as the cinematic center of the white Canadian women’s movement and their documentaries produced our understanding of the (mainly) white Canadian feminist subject to the exclusion of women of colour and First Nations women. This thesis interrogates the discursive collision between white hegemonic feminism and multicultural policy, specifically with an examination of the case study of the New Initiatives in Film Program (NIF) (1990-1996), the NFB’s first formal attempt to deal with questions of race and gender simultaneously and the representation of racial inequity within the women’s movement, as well as the discursive and historical conditions of the late 1980s/ early 1990s which led to its creation. Using archival documents and primary interviews, I employ the methods of intersectionality and counter-narrative to describe the power/knowledge nexus of white hegemonic feminism within Studio D’s institutional boundaries and the struggles for racial equity that challenged the Second Wave’s myth of a united sisterhood. In examining the successes and failures of NIF, I also demonstrate how grass-roots consciousness-raising by women of colour within the Canadian women’s movement and Studio D eventually paved the way for the NFB’s Special Mandate Team for Cultural Diversity, where the lack of non-Caucasian male filmmakers was finally addressed. I argue that the shifting relationships between notions of feminism, race and nation provide optimism for a radical possibility for transformation within Canadian cultural institutions, where diversity speak can be replaced with a foregrounding of co-existing, multiracial, and collaborative differences.
Great Power Rivalry and Macrosecuritization Failure: Why States Fail to “Securitize” Existential Threats to Humanity
Keywords: Existential Risk
Great Power Politics
International Relations
International Security
Securitization Theory

Humanity lives under a growing spectrum of existential threats that have their origins in human agency and could bring about the collapse of modern global civilization or even human extinction. Why do states fail to mobilize the will and resources to neutralize the existential threats to humankind? This dissertation develops a theory of “macrosecuritization failure,” based on securitization theory and the concept of “macrosecuritization,” and studies the empirical phenomenon of the recurrent failure of states to take extraordinary action for the security and survival of humankind. It finds great power consensus or rivalry to be the central dynamic behind the success or failure of macrosecuritization in international relations. In the absence of a world political entity with the authority and capabilities to “speak” and “do security” on behalf of humanity, the great powers collectively shape the fate of macrosecuritization and the security of humankind. The argument is that conflicting security narratives of “humanity securitization” and “national securitization”—or ways of framing the referent object, the threat, and necessary measures for security—shape the thinking and action of the great powers towards macrosecuritization. When a security narrative of humanity securitization prevails, this can open space for great power consensus on macrosecuritizaton; but when national securitization triumphs, great power rivalries lead them to prioritize national power and security over the security and survival of humankind. The dissertation examines three historical case studies of macrosecuritization (failure) in international relations: the international control over atomic energy (1942-1946), the Biological Weapons Convention (1968-1972), and artificial intelligence (2014-present). The theoretical framework posits three variables to explain the influence of conflicting security narratives over the great powers: (1) the stability of the distribution of power in the international system; (2) the power and interests of domestic securitizing actors over state audiences; and (3) the beliefs and perceptions of political leaders about threats. Ultimately, macrosecuritization fails when these conditions favour a security narrative of national securitization amongst the great powers, whereby fear of “the Other” outweighs fear of an existential threat. The argument has important implications in an age characterized by the escalating great power rivalry between the United States and China under a growing spectrum of existential threats to humanity.
Implementation of Co-clinical Autism Trials in Mice and Humans
Keywords: Animal models
Autism
Co-clinical trial
Treatment

Despite promise in animal models, novel therapeutics consistently fail in clinical trials of autism. Due to the heterogeneous nature of autism, treatment will likely only ameliorate symptoms in a subset of patients. There is a need to simultaneously test promising new compounds while understanding and predicting which patients will respond to each therapy. To determine what might contribute to response susceptibility, the implementation of co-clinical trials in autism is proposed. Here, the implementation of multiple co-clinical trials is discussed, including how changes to the protocols were expanded and adapted as the projects proceeded. The first studies set the groundwork for the methodology, first in a study of high throughput characterization of behavioural and neuroanatomical measures in mouse models, then in a study of oxytocin in mouse models of autism. Next, the first true co-clinical trial of tideglusib was investigated in mouse models of autism, followed by an investigation of arbaclofen that deviated due to treatment side effects. A high-throughput protocol for mouse models of autism is discussed, which encompasses chronic treatment over development, multiple magnetic resonance imaging time-points, and behavioural tests before, during, and after treatment. Human subjects also follow an extensive phenotyping protocol, including behavioural testing, as well as genetics and imaging assessments. This multi-modal, multi-species approach is designed to be a rigorous method of assessing treatment effect, with the intention of stratification by response susceptibility. Considerations that are key to successful implementation of a co-clinical trial are discussed, including behavioural, neuroanatomical, treatment, subject, and data analysis aspects. Recommendations based off lessons-learned are also reviewed, including the design of a third co-clinical trial. All of these considerations are discussed and implemented in a manner that makes use of the heterogeneity of the disorder-- an aspect that historically is ignored-- while also prioritizing translation across species. The implementation of co-clinical trials is the right "next step" for autism research, where the classic progression of therapeutics has failed. The hope is to introduce the concept of co-clinical trials to the field of autism, creating a shift in our current approach to the treatment of the disorder.
The Medial Prefrontal Cortex Supports Hippocampus Dependent Memory Encoding by Signaling for the Behavioral Relevance of Stimuli
Keywords: lateral entorhinal cortex
medial prefrontal cortex
memory
nucleus reuniens
rat
trace conditioning

The ability to associate related events separated in time is essential for it allows us to adapt to similar events in the future based on past experiences. The formation of this temporal associative memory (TAM) is thought to be dependent on the medial prefrontal cortex (mPFC) and hippocampus (HPC). As disruption of either region impairs the acquisition of trace eyeblink conditioning (TEBC). A TAM task wherein rats are required to form an association between a neutral conditioned stimulus (CS) and a mildly aversive unconditioned stimulus (US) across a temporal delay. In well-trained animals, mPFC neurons exhibit selective firing patterns towards the CS only when it predicts the US, possibly signaling the behavioral relevance of the CS and binding it with the US. Thus, the mPFC might support HPC-dependent memory encoding by signaling the behavioral relevance of stimuli. To address this possibility, three experiments were performed. First, to test if the relevance signal correlated with TAM acquisition, I increased the proclivity of the prelimbic (PrL) cortex to generate this relevance signal and assessed if it improved rats’ ability to acquire TEBC. Second, to investigate whether this signal’s emergence depends on afferent input into the PrL, I inactivated the lateral entorhinal cortex (LEC), an intermediary structure connected to both the PrL and HPC, that is also involved in TEBC. Lastly, as the PrL lacks monosynaptic excitatory projections to the HPC, I examined whether the relevance signal might reach the HPC via the nucleus reuniens (RE), an intermediary structure facilitating mPFC-HPC communication. I found that chemogenetic enhancement of PrL neuronal excitability improved TAM acquisition, furthermore, oscillatory activity analogous to the relevance signal correlated with the rate of TEBC acquisition. Moreover, pharmacological LEC inactivation abolished the development of the signal. Lastly, photometric recordings of PrL terminals found that the RE is a recipient of the relevance signal, suggesting that the mPFC might modulate HPC encoding via its projections to the RE. Together, these findings not only identify a prefrontal network process underlying TAM formation but also highlight the differing contributions of the LEC and the RE to corticolimbic-dependent memory formation.
Engineering Semiconductor Nanostructures for Short-Wave Infrared Detection
Keywords: Colloidal Quantum Dots
Infrared
Nanostructures
Photodetector

Photodetectors fabricated using silicon and III-V compound semiconductors enable accurate light detection across the visible and infrared spectra. These, however, suffer from limited wavelength selectivity and from manufacturing costs that prohibit wider application.Solution-processed semiconductor nanostructures such as colloidal quantum dots (CQDs) represent a promising alternative. These combine ease of processing and a bandgap that is tunable across the short-wave infrared (SWIR) spectrum. At the outset of this study, CQD photodetectors sensitive to this spectral region suffered from high dark current (10-2 mA.cm-2), poor stability (a few hours), and low detection speed (fall time of 500 ns). In this thesis, I focus on the realization and investigation of new CQD device architectures and their effects on dark current, stability, and speed. I then explore the potential benefits of CQD photodetectors over epitaxial technologies. First I investigate the limitations of prior CQD photodetectors. I find that inadequate control over the band alignment and surface passivation lead to high dark current. I pursue the development of a surface-ligand engineering strategy that tailors the functionalities of each layer, enabling me to achieve record low dark current (10-3 mA.cm-2). Next, I study two performance-limiting factors: operating stability and speed. I examine a chief cause of photodetector instability – oxygen adsorption by the electron transport layer – and develop a synthesis method with 10x lower binding energy to oxygen. The new photodetectors are stable for over 100 hours. I then develop a device model to quantify the impact of charge transport layers on the detection speed and use this to fabricate 3x faster photodetectors (fall time of 150 ns). Finally, I explore the advantages of CQD photodetectors over traditional epitaxial semiconductors. I tune the spectral response of the CQDs to a SWIR band in which atmospheric absorption suppresses solar illumination. This results in CQD photodetectors achieving 140x higher signal-to-background ratio compared to Si-based photodetector systems. I then explore the integration of CQDs onto lattice-mismatched substrates, developing an interfacial layer that improves the injection of carriers into silicon. The studies herein offer routes to improve CQD photodetector performance and demonstrate the benefits of CQDs over epitaxial technologies.
Abnormal Functional Connectivity in Descending Antinociceptive and Somatosensory Networks in People with Chronic Pain
Keywords: Ankylosing Spondylitis
Carpal Tunnel Syndrome
Chronic Pain
fMRI
Sex Differences
Treatment

One in four Canadians live with chronic pain, and women are more often affected than men. Understanding how pain-related brain networks function in people with chronic pain could provide insight on who develops this condition and why. This thesis investigated abnormal functioning of brain networks associated with ascending somatosensory input and descending pain modulation in women and men with chronic pain. I used resting state functional magnetic resonance imaging (fMRI) to measure functional connectivity (FC) and quantitative sensory testing and questionnaires to assess pain symptoms and behaviours in two chronic pain conditions; one that is more prevalent in men (ankylosing spondylitis, AS) and the other more prevalent in women (carpal tunnel syndrome, CTS). In the first study, I characterized brain-wide FC of the subgenual anterior cingulate cortex (sgACC), a key node in the descending antinociceptive system, and found sex differences both in healthy individuals and those with AS. Importantly, sgACC abnormalities were only found in women, but not men, with AS. In the second study, I investigated whether abnormal sgACC FC is unique to AS or found in women with another chronic pain condition by examining the sgACC in people with CTS. Again, I found sex differences in sgACC to whole brain FC, but abnormalities only in men with CTS, not women. Furthermore, the sgACC showed treatment-related plasticity in people with CTS who had received surgical treatment. In the third study, I measured FC in the somatosensory network, responsible for processing ascending sensory input, in people with CTS before and after surgery that significantly relieved their pain and sensory symptoms. Abnormal FC of the primary somatosensory cortex (S1) normalized, and thalamus/cortex FC was attenuated following surgery. Together, this thesis found that sex influences functional abnormalities in a key antinociceptive brain region in chronic pain; namely, abnormal sgACC FC is present in people with a chronic pain condition that is less prevalent in their sex. Furthermore, treatment can influence chronic pain-related abnormalities in ascending somatosensory pathways, and reduced FC between key nodes (thalamus and S1) may reflect central plasticity in response to the resolution of abnormal sensory signals from the periphery.
Structural Dynamics of In situ Nanofibrillated Polymer Composites
Keywords: Kinetics
Nanofibrillation
Nanomaterials
Nucleation
Physical chemistry
Polymer

In recent years, the in situ nanofibrillation method for the production of polymerpolymer composites has been explored with great interest. In this technique, large extensional flows are applied to a well-dispersed immiscible polymer blend to inducea highly elongated nanofibril morphology in the dispersed phase. It has been demonstrated that highly desirable thermomechanical and viscoelastic properties can be imparted to the composite material with only a small weight fraction of dispersed polymer nanofibrils. The in situ nanofibrillation technique presents an especially interesting avenue for research and development due to its high degree of scalability, as well as its relatively inexpensive nature compared to other techniques for the production of polymeric nanocomposites. The property changes in in situ nanofibrillated composites originate predominantly from the extremely high aspect ratio and specific surface area of the nanofibril phase. There is a large degree of interaction between the matrix and nanofibril phase due to their large interface, which induces structural changes at the nanoscale that dramatically change the behaviour of the bulk material. This thesis investigates the formation and behaviour of nanoscale structures within nanofibrillated polymer-polymer composites, and builds structure-property relationships to correlate these observations to the macroscopic behaviours of the material. The present work contributes substantially to our fundamental understanding of the physical chemistry of in situ nanofibrillated composites. The primary emphasis of this work is on the kinetics of crystal nucleation and growth at the nanofibril interface, which largely governs the structural development of the crystalline and amorphous phases. We also provide new insights into mechanical behaviours of the investigated systems, demonstrating the application of in situ nanofibrillation to induce unique functionalities in semicrystalline polymers without sacrificing mechanical performance. Within the scope of the thesis work, we also develop a novel technique employing fast scanning calorimetry to probe the kinetics of homogeneous nucleation in supercooled polymer melts.
Access to Dental Care in Canada: Organized Dentistry and the State in Two Canadian Provinces
Keywords: access
dental profession
dental program
dental therapists
organized dentistry
political influence

Although oral health in Canada has improved considerably since the 1970s, many vulnerable groups still lack proper access to dental care. Limited public funding for dental care, restricted access to private insurance, and a shortage of dental professionals in more remote parts of the country, have all contributed to historical inequality and inequity in the dental care system. Although scholarship in the field has focused substantial attention on these issues, less consideration has been given to how political forces at play influenced major policy reforms designed to improve access to basic oral care. Most notably, the political intricacies affecting the sustainability of a major dental experiment in the province of Saskatchewan—which subverted the traditional model of delivery in care in Canada—have never been analyzed through the lens of medical sociology. Through the theory of professional dominance, this thesis examines how the relationship between the dental profession and the government influenced the creation and termination of the dental therapy program in Saskatchewan, and how it foiled any initiative allowing dental therapists to work in Ontario, despite recommendations from a committee appointed by the provincial government. A scoping review examined research activity on the political influence of organized dentistry over public dental programs, and whether the professional dominance framework had been used for this purpose. A qualitative case study methodology was then adopted to examine the dental profession’s historical influence over public dental policies in Saskatchewan (1950s to 1980s), and Ontario (1960s to 1970s), through this frame. This thesis revealed that the dental professions’ political efforts, in both Saskatchewan and Ontario, were aimed at maintaining control over knowledge, and at lobbying the government for public programs focused on prevention and hygienists. This ultimately contributed to the termination of the dental therapy program in Saskatchewan and prevented the entry of dental therapists in Ontario. In applying the theory of professional dominance to dentistry, the analysis clarifies how the profession’s authority was shaped into an effective lobby that would terminate Saskatchewan’s experiment employing an alternative delivery model of oral care, and how it prevented such a model from being implemented in Ontario.
Generative Modeling with Differentiable Dynamics
Keywords: machine learning

Deep Learning has focused around building differentiable models for a variety of data modalities, but there are still some types of data that deep neural networks struggle to handle natively. In particular, data that come from high-dimensional distributions, time-stamped data that are sampled at irregular frequencies, and event-based data that exhibit both discrete- and continuous-time behaviors. These data modalities can be better modeled by specialized models with particular built-in structures. However, placing such structures within models can also come at the cost of extra computation, in both computing the output and its gradient. We will discuss tractable methods for the construction and application of generative models to high-dimensional and continuous-time data. We focus on building flexible probabilistic models that provide both an efficient algorithm for sampling and log-likelihood evaluations, as these enable simple adoption within a wide variety of machine learning applications. In the first part of this thesis, we construct unbiased gradient estimators for enabling efficient training within two foundational probabilistic modeling frameworks: 1) the Residual Flow makes use of an invertible residual network and excels at both density estimation and hybrid modeling, and 2) SUMO enables unbiased estimation of log marginal likelihoods for latent variable models, enabling them for plug-and-play applications in posterior inference and reinforcement learning. In the second part of this thesis, we present methods for dealing with discrete events localized in continuous time. We first construct a new framework for generative modeling based on ordinary differential equations (ODE) called Continuous Normalizing Flows. We then embed its usage within spatio-temporal point process modeling to build efficient yet flexible models for data from a wide variety of scientific domains. Finally, we show how to differentiate through event handling in ODE solvers, allowing us to extend Neural ODEs to cases of implicitly defined termination times and enabling learning of discrete events and discontinuous dynamics. This allows gradient-based training for switching linear dynamical systems, applicable for neuroscience and finance to decompose a complex time series into intervals.