Social determinants of health and local government: understanding and uptake of ideas in two Australian states
Bibliographic record
Abstract
OBJECTIVE: To examine the awareness and perceptions of local government staff about the social determinants of health (SDoH) and health inequity and use of these ideas to shape policy and practice. METHODS: 96 staff at 17 councils in South Australia or New South Wales responded to questions in a pilot online survey concerning: sources of knowledge about, familiarity with the evidence on, attitudes towards, and uses of ideas about the social determinants of health. Eight of 68 SA councils and 16 of 152 NSW councils were randomly selected stratified by state and metropolitan status. Differences between states and metropolitan/non-metropolitan status were explored. RESULTS: The majority of respondents (88.4%) reported some familiarity with ideas about the broad determinants of health and 90% agreed that the impact of policy action on health determinants should be considered in all major government policy and planning initiatives. Research articles, government/professional reports, and professional contacts were rated as important sources of knowledge about the social determinants of health. CONCLUSION: Resources need to be dedicated to systematic research on practical implementation of interventions on social determinants of health inequities and towards providing staff with more practical information about interventions and tools to evaluate those interventions. IMPLICATIONS: The findings suggest there is support for action addressing the social determinants of health in local government. The findings extend similar research regarding SDoH and government in NZ and Canada to Australian local government.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".