Aboriginal people in Australia and government decision making: a story that needs rewriting
Bibliographic record
Abstract
While governments in Australia and globally attempt to embrace demands from citizens for participative democracy, successive federal Governments in Australia over the last decade have often adopted an authoritarian approach to initiatives targeting Aboriginal people. Literature about effective social policy and programs points to the wisdom of ‘co-production’ of solutions with Aboriginal people. This wisdom about success being linked to meaningful and genuine consultation, indeed ‘Free, Prior and Informed Consent’ (FPIC), is also consistent with international treaties and declarations which Australia has ratified. However, consultation and FPIC are not the norms for government decision-making about Aboriginal people in Australia. Whether Aboriginal people should be consulted at all in major government decision-making is the question that federal governments ask. How can this happen in Australia? Is it legal? What are the schemes in Canada and elsewhere that might guide Australia? How can this exceptional situation in Australia be fixed?
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.045 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.011 | 0.025 |
| 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".