Unappealing: An Assessment of the Limits on Appeal Rights in Canada's New Refugee Determination System
Bibliographic record
Abstract
Canada’s refugee determination system was revised in 2012. One key feature of the new process is a quasi-judicial administrative appeal, on matters of both fact and law, at the Refugee Appeal Division (RAD) of the Immigration and Refugee Board (IRB). Under the new process, however, many claimants are denied access to the RAD.\nThis article assesses these limits on access to the RAD, drawing mostly on quantitative data obtained from the IRB and Citizenship and Immigration Canada through access to information requests. Our aim is to provide evidence-based analysis and recommendations for reform. Essentially, our conclusions are that the bars on access to the RAD are arbitrary and dangerous, and that the system should be reformed to provide access to the RAD for all refugee claimants.\nThe article proceeds in two parts. First, we set out the context for our research, explaining why access to the RAD matters. Specifically, we discuss the history of the RAD, explain how the process works, explore the difference between the appeal and judicial review, and overview the results from the revised system’s first two years of operation. Next, we examine in detail each of the bars on access to the RAD for claimants whose applications were refused at first-instance. The article ends by setting out our conclusions.
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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 | 0.034 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.023 | 0.023 |
| Scholarly communication | 0.025 | 0.009 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".