Indigenous Data Governance in Australia: Towards a National Framework
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
Australia's distinctive colonial administrative history has resulted in the generation and capture of large quantities of personal data about Indigenous Peoples in Australia, which is currently controlled and processed by government agencies and departments without coherent regulation. From an Indigenous standpoint, these data constitute stranded assets. Established legal frameworks for pursuing recovery of other classes of asset alienated by governments from Indigenous Peoples in Australia, including land, natural resources, and unpaid wages, have not yet been extended to the recovery of Indigenous data assets. This legacy scenario has created a disproportionate administrative burden for Indigenous organisations by sustaining their dependency on government for necessary data, while simultaneously suppressing the value of their own contemporary community-owned data assets. In this article, we outline leading international legal, economic, and scientific frameworks by which an equitable arrangement for the governance of Indigenous data might be restored to Indigenous Peoples in Australia.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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