Engendering Justice for Migrant Women Fleeing Violence in the Canadian Refugee Determination System
Bibliographic record
Abstract
In Canadian refugee law, women asylum seekers experience significant evidentiary hurdles, specifically the assumption that most states are able and willing to protect women from private acts of violence carried out in the home. In situating Canada's obligations towards women in search of international protection, I elucidate how the Safe Third Country Agreement between Canada and the U.S. serves as an exclusionary measure for women fleeing domestic violence in search of asylum, and aim to uncover how recent regulatory reform under the Immigration and Refugee Protection Act amounts to procedural unfairness. I closely examine how gendered asylum claims are determined in problematic ways by drawing on persuasive and legal jurisprudence at the UN level. In doing so, I critique secondary which reveals a pattern of 'superficial state protection' in the adjudication of asylum claims, whereby decision-makers fail to scrutinize the accessibility and adequacy of legislative measures and protective services in a woman's home state. Notwithstanding these valid critiques, few academics have considered whether the Immigration and Refugee Board Guideline on Vulnerable Persons can be integrated along with the Gender Guidelines in order to create an alternative policy solution that remedies the numerous obstacles that migrant women experience. I propose a specific IRB directive which adjoins each existing guideline and recognizes the legal complexities surrounding claims of gendered asylum, specifically those founded on domestic violence. My proposed guideline has the capacity to attenuate the high evidentiary standards placed on claimants at the state protection stage in the refugee determination process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.059 | 0.028 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".