Bibliographic record
Abstract
Research over the past decade in health, employment, life expectancy, child mortality, and household income has confirmed that Indigenous Australians are still Australia’s most disadvantaged group. Those residing in communities in regional and remote Australia are further disadvantaged because of the limited formal economic opportunities there. In these areas mining developments may be the major—and sometimes the only—contributors to regional economic development. However Indigenous communities have gained only relatively limited long-term economic development benefits from mining activity on land that they own or over which they have property rights of varying significance. Furthermore, while Indigenous people may place high value on realising particular non-economic benefits from mining agreements, there may be only limited capacity to deliver such benefits. This collection of papers focuses on three large, ongoing mining operations in Queensland, Western Australia and the Northern Territory under two statutory regimes—the Aboriginal Land Rights (Northern Territory) Act 1976 and the Native Title Act 1993. The authors outline the institutional basis to greater industry involvement while describing and analysing the best practice principles that can be utilised both by companies and Indigenous community organisations. The research addresses questions such as: What factors underlie successful investment in community relations and associated agreement governance and benefit packages for Indigenous communities? How are economic and non-economic flows monitored? What are the values and aspirations which Indigenous people may bring to bear in their engagement with mining developments? What more should companies and government do to develop the capacity and sustainability of local Indigenous organisations? What mining company strategies build community capacity to deal with impacts of mining? Are these adequate? How to prepare for sustainable futures for Indigenous Australians after mine closure? This research was conducted under an Australian Research Council Linkage Project, with Rio Tinto and the Committee for Economic Development of Australia as Industry Partners.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.066 | 0.018 |
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".