Not Just the Facts: Adjudicator Bias and Decisions of the Immigration and Refugee Board of Canada (2006-2011)
Bibliographic record
Abstract
The Immigration and Refugee Board of Canada (IRB) is Canada's largest administrative tribunal. The Refugee Protection Division (RPD) of the IRB is responsible for the adjudication of refugee claims made in Canada. In accordance with its obligations under international law, Canada grants protection to persons who have a well-founded fear of persecution because of race, nationality, religion, political opinion, or membership in a particular social group. In addition, a person may request protection in Canada on the basis of his or her fear of torture, risk to life or risk of cruel and unusual treatment or punishment. Acceptance (approval) rates of claims vary widely across members of the IRB, with some granting asylum in less than 10 percent of cases, and others granting asylum in more than 90 percent of cases. Despite this fact, there is a lack of analysis exploring whether grant rates vary systematically in relationship to observed characteristics of adjudicators. This paper presents statistical analysis of over 68,000 refugee claims adjudicated by 264 members of the board from 2006 to 2011. It finds that the probability of acceptance is associated with individual members' characteristics including education, gender, and professional experience, when holding constant the claimant's country of origin, gender, and the year and regional office of adjudication. The findings suggest that the identity of the adjudicator affects whether or not an individual receives asylum.
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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 | 0.059 | 0.143 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".