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Record W2300482315 · doi:10.71781/7455

Asile et genre : analyse anthropologique des demandes d’asile pour les violences de genre au Canada

2011· dissertation· fr· W2300482315 on OpenAlexaboutno aff
Isabelle Bohard

Bibliographic record

VenueOpen MIND · 2011
Typedissertation
Languagefr
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyHumanitiesLibrary sciencePolitical scienceArtComputer science

Abstract

fetched live from OpenAlex

Ce mémoire s’intéresse au changement de la notion d’asile à travers l’incorporation du concept de genre et son impact sur les processus de demande d’asile et l’octroi du statut de réfugié pour les personnes victimes de violences liées au genre au Canada. À partir d’une perspective diachronique sur les transmutations de l’asile et des transformations sociales et culturelles de ce phénomène social, nous enregistrons des tensions et des contradictions qui émanent de son application et des discours qui lui sont reliés. L’observation des dynamiques contradictoires qui s’enchevêtrent dans ce champ indique une tension dialectique entre les droits humains et la citoyenneté, une symbiose dans le développement des droits de la femme et les lois sur les réfugiés et des contradictions comme celles entre le relativisme et l’essentialisme. L’examen du processus de demande d’asile pour les femmes en particulier victimes de violences liées au genre à travers l’analyse des transformations sociales et culturelles signale le caractère éminemment politique de ce phénomène qui situe l’asile au carrefour du procès d’émancipation du sujet politique.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.093
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0170.018
Scholarly communication0.0100.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.076
GPT teacher head0.399
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicMigration, Identity, and HealthFrench-language works237,207