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Record W2131083792 · doi:10.1192/apt.bp.107.004366

Improving mental healthcare for ethnic minorities

2008· article· en· W2131083792 on OpenAlex
Kwame McKenzie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Psychiatric Treatment · 2008
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsCentre for Addiction and Mental Health
FundersUniversity of CambridgeUniversity of Central Lancashire
KeywordsEthnic groupStatutory lawMulticulturalismGovernment (linguistics)Mental healthService (business)Face (sociological concept)Public relationsMental illnessSet (abstract data type)Health careRace (biology)NursingMedicinePolitical scienceBusinessSociologyPsychiatryComputer scienceLawMarketingGender studies

Abstract

fetched live from OpenAlex

Multicultural societies offer a significant challenge to mental health services. Different groups have different rates of illness, illness models, ideas of what a suitable pathway of care is and what suitable care looks like. Trying to set up services to meet all these needs can be difficult. There may need to be modifications in clinical practice, service configuration and the way services are commissioned. Ethnic minority communities face complex problems and, consequently, strategies to deal with them can be complex, requiring support from the non-statutory sector, social services and other branches of medicine. Service development often needs research, staff training, race-equality schemes and sufficient funding to make change possible. I offer here a scheme for considering how to think through service development in this area as well as introducing the government strategy, Delivering Race Equality.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.050
GPT teacher head0.413
Teacher spread0.363 · 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