Fairness and justice in Indigenous water allocations: insights from Northern Australia
Bibliographic record
Abstract
Based on findings from participatory action research, we describe a process for the development of a Strategic Indigenous Reserve (SIR) in water for Indigenous groups in the Northern Territory, Australia. In the first case study at Mataranka, we show how a ‘top-down’ process initiated by the Northern Territory Government (NTG) was characterised by inadequate engagement and a failure to deliver water justice or an outcome accepted by the traditional owner groups. In a second case study at Oolloo, the traditional owner groups were engaged by the NTG in a consultation process, but it commenced with a unilateral offer of a water allocation to the SIR that was not formulated in a collaborative way. As a result, traditional owners considered the process unfair, and in turn, the allocation offer was perceived as ‘unfair’. Using insights from these two cases we outline an alternative and collaborative process to support engagement by decision-makers with Indigenous groups that promotes water allocations and outcomes that are just, sustainable and have broad-based community support.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.028 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| 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".