The violence of recognition: legal representation of lesbian asylum seekers in Canada’s safe haven imaginary
Bibliographic record
Abstract
This thesis examines how Canada’s refugee determination system, despite its global reputation as a “safe haven” and relatively high acceptance rate, enacts structural and psychological harms on lesbian asylum seekers. Focusing on the role of affect, narrative, and legal process, I argue that refugee determination functions as a form of legal violence through discriminatory credibility assessments, systemic violence through inconceivability and denial of the lesbian identity, and psychological violence through the retraumatization of lesbian claimants. While the Immigration and Refugee Board (IRB) has implemented Chairperson’s Guideline 9 on Sexual Orientation and Gender Identity and Expression (SOGIESC) to address discrimination, this research finds that the Guidelines are frequently ignored, misunderstood, or applied performatively. While regarded by the IRB as fool-proof mechanisms for assessing the truth of someone’s identity and lived experience, credibility assessments reproduce racialized, masculinized, and heteronormative templates of sexual identity that force claimants to perform trauma and embody Western norms of lesbian visibility in order to be seen as “authentic.” The result is a “credibility fetish” which belies what is actuality a pervasive culture of skepticism, denial, and retraumatization within the IRB that subjects’ claimants’ sexual identities to mistrust and heightened scrutiny, particularly for racialized, queer women. Drawing on thirteen semistructured interviews with immigration lawyers across Ontario and British Columbia, this thesis centers their narratives to illuminate adjudicative trends around the politics of credibility in the SOGIESC asylum process. It highlights the demands around truth, knowledge, and storytelling that lesbian asylum seekers and their legal representatives must navigate when constructing a viable claim. The research also explores the emotional toll and moral dilemmas lawyers face when working within a system that demands evidence of a particularized form of orientalist iv suffering to validate protection. This tension reflects the broader challenges faced by lesbian asylum seekers and their lawyers, where the performance of suffering and trauma becomes a form of psychic harm itself. The thesis concludes by problematizing Canada’s self-fashioning as a protector of queer and trans refugees and offers practical recommendations for lawyers and IRB decision makers aimed at reducing retraumatization and strengthening the application of the SOGIESC Guidelines.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".