Accident prevention activities: A national survey of health authorities
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 explore how health authorities in England are participating in the planning and development of accident prevention initiatives, particularly in relation to their partnership work. Design Postal questionnaire. Setting All health authorities in England. Method A questionnaire was sent to the director of health promotion/ lead officer of all the health authorities in England. They were asked for information about priorities, strategies, data collection and joint working. Results A response rate of 93 per cent was achieved. Sixty-eight per cent of districts had accidents as one of their top five priorities. A quarter (25 per cent) of districts did not have an accident prevention strategy. The majority (81 per cent), of districts were dissatisfied with their current position in relation to the collection of data. Recent changes in national policy were seen as positive to accident prevention work. However, lack of resources was seen as an important barrier. Conclusion There appears to be some considerable differences in the activities of health authorities, particularly in relation to partnership work and accident prevention strategies. Recommendations to emerge include the need for national action in relation to the collection of data, and the need for further investigation into the resource issue.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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