Segregation and Resistance Against South Asian Women with Disabilities in Ontario's Post-Secondary Education System
Bibliographic record
Abstract
The purpose of this thesis is to examine the impact of segregation and resistance on the academic achievement of South Asian women in post-secondary education with a disability based on race, gender, disability, and culture. This thesis is on students who have undertaken postsecondary education. As this thesis aims to provide a comprehensive portrait of how this marginalised group may experience systemic oppression and resistance in education, it is a comprehensive study. The primary focus of this study is to find out the effects of institutional racism and social isolation on academic achievements, as well as the agency that women of color bring to subvert oppressive systems. The data in the study are generated from interviews and focus group discussions, providing both structural and arching narratives of oppression and resistance. Early research suggests that segregation in matters of education, infrastructural barriers, and social labeling negatively affect educational status and mental health. However, the study also finds that students use daily forms of resistance in schools, such as self-advocacy, peer support, and engagement, that positively contribute to their empowerment and academic success. In doing so, this study contributes to the social research knowledge on inclusion and equity in learning institutions, with a particular focus on South Asian female learners with disabilities. It also raises the less commonly addressed but critical need for precise and targeted strategies to address the structural issues of oppression while giving a voice to oppressed groups. This thesis is grounded in the theories of intersectionality, disability, critical race theory (CRT), and anti-colonial theory, offering a multidimensional framework for understanding the systemic barriers faced by the participants. It aims to support educators, policymakers, and activists in developing and enhancing just and equitable learning environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".