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Record W2801257720 · doi:10.32920/22341148

Refugee Law’s Fact-Finding Crisis: Truth, Risk, and the Wrong Mistake

2023· preprint· en· W2801257720 on OpenAlexaboutno aff
Hilary Evans Cameron

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeRefugee lawLawMistakeConventionPolitical scienceBlameGlobeNormativeJurisprudenceLaw and economicsCriminologySociologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

<p>At a time when many around the world are fleeing their homes, seeking refugee protection has become a game of chance. Partly to blame is the law that governs how refugee status decision-makers resolve their doubts. This long-neglected branch of refugee law has been growing in the dark, with little guidance from the Refugee Convention and little attention from scholars. By looking closely at the Canadian jurisprudence, Hilary Evans Cameron provides the first full account of what this law is trying to accomplish in a refugee hearing. She demonstrates how a hole in the law's normative foundations is contributing to the dysfunction of one of the world's most respected refugee determination systems, and may well be undermining refugee protection across the globe.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.107
GPT teacher head0.365
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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