Ageing and Mental Health in Canada: Perspectives from Law, Policy, and Longitudinal Research
Bibliographic record
Abstract
Canada is a relatively young, geographically-diverse country, with a larger proportion of the population aged over 65 than under 15. Increasing alongside the number of ageing Canadians is the number of older adults that live with mental health challenges. Across the life course, one in five Canadians will experience a mental health disorder with many more living with subclinical symptoms. For these individuals, their lived experience may be directly impacted by the contemporary laws and policies governing mental illness. Examining and reviewing the historical context of mental health and older adults, we provide insights into the evolving landscape of Canadian mental health law and policy, paternalistic roots in the infancy of the country, into modern foci on equity and diversity. Progressing in parallel to changes in mental health policy has been the advancement of mental health research, particularly through longitudinal studies of ageing. Although acting through different mechanisms, the evolution of Canadian mental health law, policy, and research has had, and continues to have, considerable impacts on the substantial proportion of Canadians living with mental health challenges.
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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 | 0.027 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.037 | 0.021 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".