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Record W7159902037

La santé mentale des minorités visibles à Montréal au prisme de l’hostilité du quartier

2025· other· fr· W7159902037 on OpenAlexaboutno aff
Chedeline Cherifin Ariste

Bibliographic record

VenueEspaceINRS (National Institute for Scientific Research (Canada)) · 2025
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationContext (archaeology)Mental healthIdentity (music)Hostility
DOInot available

Abstract

fetched live from OpenAlex

Ce mémoire explore l'association entre l'hostilité du quartier et la santé mentale des minorités visibles à Montréal. Il propose une conceptualisation originale de l'« hostilité du quartier » structurée en trois dimensions interdépendantes : matérielle, systémique et perçue. L'adoption conjointe du modèle socio-écologique et de l'approche intersectionnelle met en lumière les interactions entre caractéristiques individuelles et contextuelles et des expériences différenciées selon la racialisation. Cette recherche comble une lacune de la littérature canadienne, où les travaux sur la santé mentale des minorités visibles articulent rarement les dimensions spatiales, les rapports sociaux de racialisation et l'approche intersectionnelle. Les analyses quantitatives, menées sur un échantillon de 1 119 Montréalais·es (dont 284 personnes de minorités visibles) à partir des données de l'Enquête sur la santé dans les collectivités canadiennes (ESCC 2015), et de données sur le quartier de l'Enquête sociale générale (ESG 2014), révèlent que les minorités visibles et les femmes déclarent une santé mentale moins favorable. Les modèles stratifiés indiquent des associations différenciées : la discrimination dans le quartier est liée à la santé mentale des minorités visibles, tandis que le désordre social et physique l'est pour les non-minoritaires. L'étude souligne la nécessité de dépasser les approches centrées sur la seule défavorisation socio-économique et d'orienter des politiques intégrant les caractéristiques du quartier (désordre social et physique, discrimination, sécurité), ainsi que le développement de services culturellement sécuritaires. This thesis explores the association between neighborhood hostility and the mental health of visible minorities in Montreal. It proposes an original conceptualization of “neighborhood hostility” structured around three interdependent dimensions: material, systemic, and perceived. The joint adoption of a socio-ecological model and an intersectional approach highlights the interactions between individual and contextual characteristics and experiences that differ according to racialization. This research fills a gap in the Canadian literature, where studies on the mental health of visible minorities rarely articulate spatial dimensions, social relations of racialization, and the intersectional approach. Quantitative analyses conducted on a sample of 1,119 Montrealers (including 284 visible minorities) based on data from the Canadian Community Health Survey (CCHS 2015), and on neighborhood data from the General Social Survey (GSS 2014), reveal that visible minorities and women report poorer mental health. Stratified models indicate differentiated associations: discrimination in the neighborhood is linked to the mental health of visible minorities, while social and physical disorder is linked to that of non-minorities The study highlights the need to move beyond approaches focused solely on socioeconomic disadvantage and to develop policies that take into account neighborhood characteristics (social and physical disorder, discrimination, safety), as well as the development of culturally safe services.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.030
GPT teacher head0.329
Teacher spread0.299 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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Same venueEspaceINRS (National Institute for Scientific Research (Canada))French-language works237,207