Who Controls the Images of Women Refugees?
Bibliographic record
Abstract
The gender guidelines for asylum determination are the legal instrument expected to compensate for silence concerning gender-related persecution in the Refugee Convention. This paper focuses on Canadian and US decisions concerning gender-related asylum cases in order to examine the effects and functions of these guidelines. My argument centers on the cases of Muslim women who sought asylum from gender-related persecution, supposedly caused by their 'oppositional' or 'unfavorable' attitudes or opinions towards the code of dressing, conduct or ethics of Muslim societies. By studying the description of these women refugees in asylum decisions, I show how they are defined as 'victims of Islam' and how their image as vicims is then used to convey a negative image of Islam. The case of Nada, an asylum seeker to Canada, is especially striking, because the media portrayal of Nadia's case was effectively controlled by the host country, while the Nadia's own view of Islam was both ignored and denied. Muslim websites and Muslim feminist writers persuasively expose the problematic issues that arise from such cases. This investigation leads me to raise questions about the humanitarian effects and functions of the gender guidelines. Indeed, the guidelines may have a detrimental function by fostering negative stereotypes of Islam.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".