Public administration reform for Aboriginal affairs: An institutionalist analysis
Bibliographic record
Abstract
Abstract Persistent underperformance of public policy and program implementation in Aboriginal affairs is widely recognised. We analysed the results of two case studies of attempted reforms in public administration of Aboriginal primary health care in the Northern Territory, using a framework based on the institutionalist and systemic racism literatures, with the aim of better understanding the sources of implementation failure. Implementation of the agreed reforms was unsuccessful. Contributing factors were as follows: strong recognition of the need for change was not sustained; the seeds of change, present in the form of alternative practices, were not built on; there was a notable absence of sustained political/bureaucratic authorisation; and, interacting with all of these, systemic racism had important consequences and implications. Our framework was useful for making sense of the results. It is clear that reforms in Aboriginal affairs will require government authorities to engage with organisations and communities. We conclude that there are four requirements for improved implementation success: clear recognition of the need for change in ‘business as usual’; sustainable commitment and authorisation; the building of alternative structures and methods to enable effective power sharing (consistent with the requirements of parliamentary democracy); and addressing the impact of systemic racism on decision‐making, relationships, and risk management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".