Protecting Those Who Go Beyond the Law: Contemplating Refugee Status for Individuals Who Challenge Oppression Through Resistance
Bibliographic record
Abstract
A discrete phenomenon has been emerging within the practice of refugee law whereby individuals who engage in acts of resistance waged against oppression in their countries of nationality have either been granted asylum or have had their actions recognized as forms of political opinion making them eligible for asylum. Through an examination of the decisions of administrative adjudicators and appellate judges in various jurisdictions, this article argues that three significant observations emerge from such case law. First, the decisions demonstrate the capacity of individuals to challenge injustices and oppression through an interpretation of applicable legal and ethical principles followed by their enforcement. These decisions also illustrate the capacity of individuals to act as transformative human agents within the international legal system, even if incapable of being recognized as full legal persons under international law. Second, the decisions represent an important legitimization of and support for such acts of resistance, even if implicit. Third, granting asylum to individuals who have engaged in resistance also challenges a deeply ingrained tendency to view refugees as idealized and/or hapless victims who have been attacked for some immutable characteristic, rather than those who take albeit provocative but justified actions and who as a consequence face victimization.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.038 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".