Bibliographic record
Abstract
At least 5 percent of Canada's population suffers from a serious mental illness such as schizophrenia or bipolar disorder. While recent years have seen many changes and, arguably, improvements concerning how society responds to the mentally ill, there remain divisions of opinion among stakeholder groups regarding the way mental health services are delivered. Community Mental Health in Canada is a timely, critical overview of public mental health services in Canada, looking at where we have come from, the current situation, and where we may be heading. Simon Davis examines the prevalence and impact of mental illness in Canada, and how public treatment programs define their eligibility criteria. He explicates the complementary and conflicting interests of stakeholder groups - mental health professionals, clients, families, government, and drug companies - and examines initiatives in treatment, rehabilitation, housing, and criminal justice programs with reference to the best practices literature. Davis also includes chapters on the clinical benefits and costs of particular interventions, the recovery model, diversity and cultural competence, and the legal and ethical basis of mental health practice, particularly as it applies to the use of coercion and involuntary treatment. Community Mental Health in Canada offers an understanding both of clinical mental health practice and the structural context in which it is situated. This book will be a valuable resource for senior level undergraduates starting or considering a career in health care, while also providing a useful overview to others interested in the way we provide services to our most vulnerable citizens.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.019 | 0.023 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".