A Canadian model of work integration for persons with mental illnesses
Bibliographic record
Abstract
PURPOSE: The many programmes, services and policy initiatives that focus on work integration for persons with mental illnesses and psychiatric disabilities reflect a multitude of beliefs and practices that lead the field to work in divergent, sometimes conflicting directions. This article presents a framework of the central constructs that dominate the field of work integration and mental illness. METHOD: Using the principles of constructivist grounded theory, an analysis of Canadian documents was conducted; the sample was comprised of 100 academic publications, 76 government documents, 138 popular press, 5 legal papers and 107 documents from work initiatives across Canada. In addition, semi-structured interviews were conducted with 19 key informants from across Canada. RESULTS: Five central perspectives were identified, around which the field of work integration currently operates: a competency perspective; a citizenship perspective; a workplace health perspective; a perspective focussing on potential, growth and self-construction; a community economic development perspective. CONCLUSIONS: Uncovering the varied discourses around work integration enables an understanding of the different ways in which the problem of work integration has come to be seen in today's context; how it is understood, spoken about, dealt with and internalised by individuals and groups. The framework sheds light on the rationale for the range of solutions that have been developed to address the problem of work integration, and it is useful in the analysis of how policy, practice and research initiatives are shaped and promoted.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".