MétaCan
Menu
Back to cohort
Record W2770498450 · doi:10.3138/cjwl.29.2.290

Denying Refugee Protection to LGBTQ and Marginalized Persons: A Retrospective Look at State Protection in Canadian Refugee Law

2017· article· en· W2770498450 on OpenAlexaboutno aff
Jamie Liew

Bibliographic record

VenueCanadian Journal of Women and the Law/Revue Femmes et Droit · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeRefugee lawDue diligenceLawPlaintiffPolitical scienceState (computer science)International lawLaw and economicsSociology

Abstract

fetched live from OpenAlex

Canadian refugee law has evolved substantially in the last two decades, especially when it comes to making findings of whether a state provides protection to a refugee claimant. Canadian refugee law is making problematic presumptions, increasing burdens on claimants, asking claimants whether they have done their due diligence, and accepting just the best efforts of a state to assuage concerns that protection is necessary. All of these measures have been adopted without consideration as to the true object and purpose of the refugee protection regime and the international law principles that support this regime. Currently in Canada, there is not only confusion as to what the refugee definition calls for in terms of assessing state protection but also the inconsistent application of various approaches, which gives rise to concerns that legitimate refugee claimants are being denied protection, especially those who make claims based on gender and sexual orientation. This article argues that the integrity of Canada's refugee protection regime is at stake and decision makers and judges should reconsider the path Canada has taken since Canada v Ward. The recommendation in this article is to eliminate presumptions, do away with the expectations that claimants need to exercise all due diligence, and accept nothing but effective state protection.

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)0.003
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: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Women and the Law/Revue Femmes et DroitSame topicMigration, Refugees, and IntegrationFrench-language works237,207