Sin of Omission: Exploring a Key Credibility Inference in Canadian Refugee Status Rejections
Bibliographic record
Abstract
Refugee claimants in Canada must submit a “Basis of Claim” form to the Refugee Board before attending a hearing with the adjudicator who will decide their claim. On this form, they are expected to produce a written narrative that explains “everything that is important” about their experiences. At their hearing, many claimants encounter, for the first time, a key principle of Canadian refugee law: The omission of any “important information” from this narrative suggests that they have invented their claim. This study takes a close look at how this “omission from the narrative” inference is operating within a set of judgments by Canadian refugee status adjudicators. It provides the first quantitative overview of the role that this inference plays in a sample of Canadian decisions as well as the first in-depth analysis of this kind of high-stakes legal reasoning. Negative credibility findings were at the heart of the decision to reject a large majority of the claimants in these decisions (72 per cent; 217/303), and the adjudicators in these cases relied on an “omission from the narrative” inference in almost half of the decisions in which they concluded that the claimant was lying (49 per cent; 128/259). The major premise underlying this inference is that, in drafting their narrative, the claimant would have understood what information the Board expected them to provide. The claimants in these decisions raised strong challenges to this premise, and the adjudicators did not identify compelling support for it. At least in the context in which it currently operates in Canadian refugee hearings, adjudicators cannot, therefore, reliably infer deception from the fact that a claimant has added even important new information at the hearing. This conclusion has implications for the Canadian refugee system’s administrators; for adjudicators; for appellate-level decision makers and judges; for legal aid systems; for counsel who represent refugee claimants; and for researchers who study refugee status adjudication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".