The Institution of Gender-Based Asylum and Epistemic Injustice: A Structural Limit
Bibliographic record
Abstract
One of the recent attempts to explore epistemic dimensions of forced displacement focuses on the institution of gender-based asylum and hopes to detect forms of epistemic injustice within assessments of gender related asylum applications. Following this attempt, I aim in this paper to demonstrate how the institution of gender-based asylum is structured to produce epistemic injustice at least in the forms of testimonial injustice and contributory injustice. This structural limit becomes visible when we realize how the institution of asylum is formed to provide legitimacy to the institutional comfort the respective migration courts and boards enjoy. This institutional comfort afforded to migration boards and courts by the existing asylum regimes in the current order of nation-states leads to a systemic prioritization of state actors’ epistemic resources rather than that of applicants, which, in turn, results in epistemic injustice and impacts the determination of applicants’ refugee status.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.058 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".