Bibliographic record
Abstract
In recent years, cultural competence has become a popular term for a variety ofstrategies to address the challenge of cultural diversity in mental health services.This issue of Transcultural Psychiatry presents papers from the McGill AdvancedStudy Institute in Cultural Psychiatry on ‘‘Rethinking Cultural Competencefrom International Perspectives,’’ which was held in Montreal, April 27and 28, 2010. Selected papers from the meeting have been supplemented withother contributions to the journal that fit the theme. Taken together, thesepapers show how conceptual analysis and critique of cultural competence canpoint toward ways to improve the cultural responsiveness, appropriateness andeffectiveness of clinical services, and in doing so contribute to reducinghealth disparities.Cultural diversity poses challenges to mental health services for many reasons.Culture influences the experience, expression, course and outcome of mentalhealth problems, help-seeking and the response to health promotion, preventionor treatment interventions. The clinical encounter is shaped by differencesbetween patient and clinician in social position and power, which are associatedwith differences in cultural knowledge and identity, language, religion and otheraspects of cultural identity. Specific ethnocultural or racialized groups may sufferhealth disparities and social disadvantage as a result of the meanings and mater-ial consequences of their socially constructed identities. In some instances, cul-tural processes may create or constitute unique social and psychological problemsor predicaments that deserve clinical attention. In culturally diverse societies,the dominant culture, which is expressed through social institutions, includingthe health care system, regulates what sorts of problems are recognized and whatkinds of social or cultural differences are viewed as worthy of attention.A large literature shows the importance of social determinants of healthincluding social status, employment, education, wealth and social support
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.025 | 0.200 |
| Scholarly communication | 0.023 | 0.039 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.008 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".