The Complexity of Determining Refugeehood: A Multidisciplinary Analysis of the Decision-making Process of the Canadian Immigration and Refugee Board
Bibliographic record
Abstract
Refugee determination is one of the most complex adjudication functions in industrialized societies. In Canada, despite a relatively broad recognition rate and a teleological interpretation of the international refugee definition, dissatisfaction with the decision‐making process at the Immigration and Refugee Board (IRB) has been expressed by numerous actors. This paper documents the influence of legal, psychological and cultural factors on the process of refugee determination. Forty problematic cases referred to the research team by professionals were studied using both quantitative and qualitative approaches. The results indicate numerous problems affecting the role and behaviour of all actors: difficulties in evaluating evidence, assessing credibility, and conducting hearings; problems in coping with vicarious traumatization and uncontrolled emotional reactions; poor knowledge of the political context, false representations of war, and cultural misunderstandings or insensitivity. In a majority of cases, these legal, psychological and cultural dimensions interact together, often impacting negatively upon Board Members' ability to evaluate credibility and upon the overall conduct of hearings. These findings suggest that the refugee determination process might benefit from revised selection criteria for Board Members and refugee claim officers, as well as improved training and support for all actors.
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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 | 0.023 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.024 | 0.021 |
| Scholarly communication | 0.021 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".