Contracting for Indigenous Health Care: Towards Mutual Accountability
Bibliographic record
Abstract
In Australia and other industrialised countries, governments contract with the non‐government sector for the provision of primary health care to indigenous peoples. Australian governments have developed policies and funding programs to support this health sector, but the current arrangements are unduly complex and fragmented. The results of our study show that the complex contractual environment for Aboriginal Community‐Controlled Health Services (ACCHSs) and their funders is an unintended but inevitable result of a quasi‐classical approach to contracts applied by multiple funders. The analysis in this article highlights potential policy and program changes that could improve the effectiveness of funding and accountability arrangements, based on the use of an alliance contracting model, better performance indicators and greater clarity in the relative roles of national and jurisdictional governments.
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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 | 0.110 | 0.166 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".