Reducing the impact of unemployment on health: revisiting the agenda for primary health care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To identify potentially effective strategies to be used in the primary health care (PHC) setting to prevent, detect and manage the health problems of unemployed people. DESIGN: A narrative review of articles on PHC-based interventions for unemployed people that were published during the period January 1985 to February 2009. RESULTS: Seven articles with a focus on improving the health of unemployed people through assessment, management and referral within PHC settings were identified. Four were based in Australia, and the others were from Canada and Europe. Most described interventions that incorporated strategies aimed at increasing general practitioners' awareness of the health problems of unemployed people and providing guidance on the management of these problems. One article included an evaluation of the impact of the intervention on health and social outcomes, but no impact was shown. CONCLUSIONS: There have been few formal scientific investigations into the effectiveness of PHC-based interventions for unemployed people. GPs and other community health workers have a central role in preventing, and providing early management of, the health problems of unemployed people, and supporting return to work. People who are unemployed have poorer physical and mental health than those who are employed. Research should move from describing these health problems to developing interventions that are subject to rigorous evaluation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it