MétaCan
Menu
Back to cohort
Record W2003420303 · doi:10.3138/cjwl.26.2.05

Taking It Personally: Delimiting Gender-Based Refugee Claims Using the Complementary Protection Provision in Canada

2014· article· en· W2003420303 on OpenAlexaboutno aff
Jamie Liew

Bibliographic record

VenueCanadian Journal of Women and the Law/Revue Femmes et Droit · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeDenialPersecutionCriminologyCovertTortureOppressionPerformative utteranceRefugee lawLawPolitical scienceSociologyHuman rightsPsychology

Abstract

fetched live from OpenAlex

Random violence and general criminal risk—decision makers evaluating refugee claims are characterizing violence against women in this manner. The reduction of gendered violence, leading to the denial of refugee claims, occurs under the covert operation of Canada’s consolidated refugee definition. Canada has received accolades for recognizing gender-related persecution. Since this recognition, Canada has consolidated its refugee definition, legislating a “complementary protection provision” in the Immigration and Refugee Protection Act. Prior to 2002, risk assessments done just prior to the removal of persons asked whether persons would be returned to torture or cruel and unusual punishment. In 2002, this assessment was included in the refugee determination process. There has been little evaluation of this provision since then. This article examines the performative functions of Canada’s complementary protection and finds the provision delimits gender-related claims in three ways. First, it does not fill the gaps left by the enumerated grounds system. Second, the provision encourages the production of harmful discourse on violence against women. Finally, it encourages decision makers to conflate the separate analyses (enumerated grounds and the complementary protection schemes), erroneously allowing factors such as the universality of oppression or violence to erode the enumerated grounds regime.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.084
GPT teacher head0.287
Teacher spread0.203 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Women and the Law/Revue Femmes et DroitSame topicGender, Security, and ConflictFrench-language works237,207