Privacy Protection and the Confidentiality of Psychiatric Health Care Records
Bibliographic record
Abstract
Mental health issues pose critical challenges for Canada's systems of justice and health care. Problems with mental health are common, but often neglected due to stigma and the vulnerability of those living with these conditions. This is evident within our legal system. Every day in our courts we see played out the struggle to protect the human rights and dignity of individual Canadians with mental health challenges, to access adequate mental health care and social support, and to provide genuinely helpful responses to criminal behaviour associated with mental health problems. Law and Mind: Mental Health Law and Policy in Canada provides a comprehensive analysis of the most important cases and key debates at the intersection of mental health law and policy.\nWritten by a group of Canada's leading experts on mental health law, this volume provides practitioners, researchers and policy-makers with valuable insight into this challenging and important area of the law.\nFeatures and benefitsLaw and Mind: Mental Health Law and Policy in Canada is an important resource for understanding the complexities of mental health law and related policy issues in Canada.\nLaw students, practising lawyers and policy-makers alike will benefit from the broad range of topics covered in this comprehensive text. Topics addressed include the law surrounding the funding and administration of mental health care in Canada, the principles of mental health law related to hospitalization and consent to treatment, the components of the criminal law of mental disorder, and mental health issues in the policing and correctional contexts. In addition, the authors offer focused treatment of mental health law issues facing specific populations, including children, the elderly, refugees and ethnic minorities.\nThis text is written by leading mental health law experts who bring years of practice, research and expertise to provide readers with a comprehensive resource which: Presents the legal issues related to mental health in a comprehensive manner Enables students and lawyers to learn this challenging subject matter quickly and effectively Analyzes recent changes and developments in the law Provides current information so lawyers can properly advise their clients Discusses pressing and emerging mental health issues that are relevant to practitioners and their clients \nEssential readingThis new release will be particularly useful for: Health lawyers advising clients and in-house lawyers at health service providers as it is an up-to-date resource on mental health law and policy Students looking for a comprehensive resource on mental health law written by leading academics Government health workers and policymakers who need to consult a reliable reference volume Law libraries that want to stock essential guides for lawyers and students
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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 | 0.033 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".