“Do-Live-Well”: A Canadian framework for promoting occupation, health, and well-being
Bibliographic record
Abstract
BACKGROUND: Occupational therapists can bring a unique and valuable perspective to the national dialogue on health promotion. Current approaches have a narrow focus on diet and exercise; a broader focus on occupation has the potential to enrich understanding regarding forces that contribute to health and well-being. PURPOSE: A new "Do-Live-Well" framework will be presented that is grounded in evidence regarding the links between what people do every day and their health and well-being. KEY ISSUES: Elements of the framework include eight different dimensions of experience and five key activity patterns that impact health and well-being outcomes. Personal and social forces that shape activity engagement also affect the links to health and well-being. IMPLICATIONS: The framework is designed to facilitate individual reflection, community advocacy, and system-level dialogue about the impact of day-to-day occupations on the health and well-being of Canadians.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.028 | 0.055 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".