Indigenous communities and climate change: a Recognition, Empowerment and Devolution (RED) framework in the Murray-Darling Basin, Australia
Bibliographic record
Abstract
Climate change directly threatens Indigenous cultures and livelihoods across Australia's Murray-Darling Basin (MDB). Using a modified grounded theory methodology, this study draws on in-depth interviews with Indigenous leaders and elders across the MDB to highlight that climate variability and over-extraction of water resources by agricultural users directly threatens the integrity of aquatic systems. As a consequence, Indigenous cultures and livelihoods reliant on these natural systems are at risk. Interviewees identify a range of systemic barriers that entrench vulnerability of Indigenous Peoples (IPs) in the MDB. Building on insights from the literature and from interviews, a Recognition, Empowerment and Devolution (RED) framework is developed to establish possible pathways to support climate adaptation by rural IPs. Fundamental to this RED framework is the need for non-Indigenous socio-institutional structures to create a ‘space’ to allow IPs the ability to adapt in their own ways to climate impacts.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".