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Record W4404067744 · doi:10.7202/1114158ar

Stratégies d’intégration et de support en santé mentale des immigrants francophones au Canada anglais

2024· article· fr· W4404067744 on OpenAlexaffvenueabout
Hélène Archambault, Danielle de Moissac, Raymond Tempier

Bibliographic record

VenueMinorités linguistiques et société · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsInstitut du Savoir MontfortUniversité de Saint-Boniface
Fundersnot available
KeywordsImmigrationHumanitiesPolitical scienceSociologyPsychologyArt

Abstract

fetched live from OpenAlex

Cet article explore les stratégies d’intégration au système de santé telles que proposées par des personnes immigrantes francophones au sein de communautés francophones en situation minoritaire au Canada (CFSM). Une recherche qualitative par entrevues semi-dirigées a été menée dans trois villes canadiennes auprès de soixante personnes adultes immigrantes ou réfugiées. Centrées sur les représentations des personnes immigrantes quant aux services de soutien en santé mentale, diverses stratégies ont été dégagées. La préparation prémigratoire et le regroupement des informations sous un guichet unique semblent contribuer à une intégration réussie. L’appui des organismes communautaires et des autorités religieuses est bénéfique pour le soutien informationnel et socioémotionnel des nouveaux arrivants, ayant des retombées positives sur leur bienêtre et leur capacité de s’intégrer à leur nouveau milieu de vie.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.005
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.376
Teacher spread0.354 · 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 designNot applicable
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
Published2024
Admission routes3
Has abstractyes

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Same venueMinorités linguistiques et sociétéSame topicMigration, Identity, and HealthFrench-language works237,207