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Record W2198866309 · doi:10.4000/ideas.1158

Immigrer, mourir et vivre un deuil au Canada : contexte légal, stratégies et réseaux transnationaux

2015· article· fr· W2198866309 on OpenAlexaffabout
Lilyane Rachédi Drapeau, Laura Chéron-Leboeuf, Béatrice Halsouet, Michèle Vatz-Laaroussi

Bibliographic record

VenueIdeAs · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)SNC-Lavalin (Canada)Université du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article porte sur le sujet de la mort et du deuil en contexte migratoire. Il repose sur deux recherches qualitatives menées sur le territoire du Québec au Canada. La première a permis de rencontrer des femmes et hommes endeuillés, des informateurs clés de religions chrétienne, musulmane et hindoue. La deuxième porte sur les transmissions intergénérationnelles de trios générationnels de femmes réfugiées. Les principaux résultats présentés mettent en avant l’importance des pratiques rituelles funéraires lorsque la perte d’un être cher se produit dans la société d’accueil. Cependant, le respect et l’application de ces pratiques dépendent du cadre juridique de la société d’accueil. Les personnes endeuillées s’adaptent alors et développent des stratégies pour maintenir les pratiques les plus significatives. Enfin, le discours des femmes réfugiées nous amène à porter un autre regard sur l’investissement des réseaux transnationaux et la migration lors de l’événement de la mort et du deuil.

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)0.004
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 score0.058
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0280.020
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.036
GPT teacher head0.326
Teacher spread0.290 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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