Accommodating Vulnerable Claimants in the Refugee Hearing: The Canadian Example
Bibliographic record
Abstract
Abstract The Canadian protection regime has made many positive steps towards the recognition of migrant vulnerability. For example, Chairperson’s Guideline 8 from the Immigration and Refugee Board (IRB) was developed in 2006 (and subsequently revised over the years) to assist Canadian decision-makers to provide procedural accommodation(s) (e.g., priority processing of application, allowing a support person, or varying the order of questioning—accommodations that impact the process of the hearing, not the substantive outcome) for vulnerable individuals who are going through Canada’s inland refugee determination process. However, as is discussed in this chapter, our research found that practitioners, and even civil servants, have mixed perspectives on the success of translating this awareness into effective action. Despite these developments, refugee claimants are facing several challenges in asserting or ‘proving’ vulnerability and thus eligibility for procedural accommodation. Of particular concern is the difficulty with accessing psychological assessments for psychologically vulnerable asylum seekers and their inconsistent consideration by decision makers. Another key concern is the discretion exercised by decision-makers, both in terms of acknowledging vulnerability and in terms of determining what, if any, procedural accommodations are appropriate. While recent changes to Guideline 8 suggest a desire to address some of the challenges presented here, it remains to be seen whether this effort will be successful.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".