Bibliographic record
Abstract
Abstract Article 1F(b) of the 1951 Convention relating to the Status of Refugees denies refugee protection to persons who have committed a “serious non-political crime.” In Febles v. Canada (Citizenship and Immigration), 2014 SCC 68, a majority of the Supreme Court of Canada held that the “seriousness” of a crime is to be determined based on the offence at the time it was committed. Later developments, such as serving a sentence or rehabilitation, do not factor in the analysis. Febles remains the leading apex court decision on determining seriousness. We argue the majority’s analysis creates the potential for both material and epistemic injustice. We then rewrite Febles by drawing on criminal law theory and a variety of critical perspectives, most notably critical race theory, decolonial theory, and Third World Approaches to International Law. On our rewrite, crimes meet the threshold of “seriousness” if they represent an intrinsic threat to the civil order of any State, hence indirectly a threat to the international order. Exclusion holds refugee status in abeyance until the goals of criminal justice have been met with respect to such crimes. If they have, either through formal or informal means, a claimant should not be excluded.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".