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Record W2254499662 · doi:10.7870/cjcmh-2010-0025

Community Mental Health Organizations in Ontario: Perceptions of Cultural Responsiveness

2010· article· en· W2254499662 on OpenAlexafffundvenueabout
Anne Westhues, Rich Janzen, Don Roth, Jill G. Grant

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of WindsorCanadian Mental Health AssociationCentre for Community Based ResearchCommunity Based Research CentreWilfrid Laurier University
FundersOntario Trillium Foundation
KeywordsMental healthPerceptionPublic relationsWork (physics)PsychologyService (business)Baseline (sea)Mental health serviceCultural issuesCultural diversitySociologyPolitical scienceBusinessMarketingPsychiatryEngineering

Abstract

fetched live from OpenAlex

This paper reports the findings from an online survey that explored the perceptions of 111 leaders within community mental health organizations in Ontario about how responsive they are to the service needs of people from diverse cultural-linguistic groups. The findings show that more than half of respondents said they engaged in 20 of the 27 practices that promote cultural responsiveness. Comparisons of community organizations with different service philosophies found only one difference in terms of engaging in culturally responsive practices. Specifically, the difference was in whether or not staff received ongoing training in how to work with people from the cultural-linguistic groups the organization serves. These data provide a baseline against which progress can be measured toward greater cultural responsiveness in community mental health organizations in 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.377
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 teacher head, not a consensus.

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

Citations4
Published2010
Admission routes4
Has abstractyes

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