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Record W2794129769 · doi:10.7202/1043497ar

L’offre active de services de santé mentale en français en Ontario : données et enjeux

2018· article· fr· W2794129769 on OpenAlexaffvenueabout
Linda Cardinal, Martin Normand, Alain P. Gauthier, Rachel Laforest, Suzanne Huot, Denis Prud’homme, Marcel Castonguay, Marie-Hélène Eddie, Jacinthe Savard, Sanni Yaya

Bibliographic record

VenueMinorités linguistiques et société · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsHome and Community Care Support ServicesQueen's UniversityLaurentian UniversityInstitut du Savoir MontfortUniversity of Ottawa
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Au Canada, au gouvernement fédéral et dans plusieurs provinces, le principe d’offre active sert à guider la prestation des services publics en français. L’Ontario se démarque, car son approche est en partie volontaire. Il importe donc d’étudier comment les services en français sont intégrés à la gouvernance des services publics au sein de la province. Cet article puise dans les données gouvernementales existantes afin de brosser un tableau de l’offre active de services en français en santé mentale. Or, les auteurs montrent que ces données sont difficiles à obtenir et parcellaires. L’article sert à souligner des défis importants pour l’offre de services en français dans le domaine de la santé mentale en Ontario.

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)0.013
metaresearch head score (Gemma)0.050
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 score0.073
Threshold uncertainty score0.531

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.021
Science and technology studies0.0070.003
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.060
GPT teacher head0.461
Teacher spread0.401 · 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

Citations10
Published2018
Admission routes3
Has abstractyes

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