Working with cultural diverse persons involved in law and mental health - cultural competency training manual
Bibliographic record
Abstract
The goal of this presentation is to introduce a new “Cultural Competency Training/Manual (CCTP) for Law and Mental Health professionals Working with persons involved with law and mental health” sponsored by a grant from the Law Foundation of Ontario and department of psychiatry of Mount Sinai Hospital. The manual is qualitative which includes conducting a literature review, facilitation of multi-stakeholder focus groups, and interviewed key stakeholders, consultation with clinical staff from the Mount Sinai Hospital and other Court Support programs, to address the key challenges in working with culturally diverse persons involved with law and mental health. In the oral presentation, we will present key themes on the challenges in dealing with culturally-diverse persons involved in law and mental health. The themes were consistent with the literature, evidence-based research, and validated by actual provider experience. They include language and communication, mistrust of mainstream services, racism and discrimination, resistance from persons involved with law and mental health and their families, and the need for cultural competency practices, such as interpretation, cultural understanding, community and systemic support. With these themes in mind, we will demonstrate the application of practical skills and cultural competencies using vignettes. A cultural competency model of working with culturally diverse persons involved in law and mental health and the five key responsibilities will be introduced. They include the following domains: language and communication, system support and navigation, education and advocacy, and collaboration.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".