Investing in Indigenous Natural Resource Management
Bibliographic record
Abstract
\n \t\t\tThis book assesses the case for investing in Indigenous natural resource management (NRM) in tropical Australia. Indigenous people provide a number of public goods in relation to environmental management for which they are not remunerated. Their presence on country should be viewed as a national asset. The health of Australia's Indigenous people remains unacceptable. Individual and collective engagement with ancestrally significant land and sea improves health outcomes, while also supporting individual autonomy and social cohesion through cultural practices. This book brings together a broad suite of authors with an understanding of Indigenous NRM and the economics thereof. Indigenous NRM emerges as a 'keystone policy area' that could allow integration of many policy fields commonly considered in isolation. The editors of this book all have wide experience in the fields covered by this book. Professor Marty Luckert from the University of Alberta has been offering insights into the economics of environmental management around the world for decades, Professor Bruce Campbell from Charles Darwin University (CDU) has an international reputation for his work on livelihoods among the rural poor, Julian Gorman (CDU) has played a key role in fostering wildlife-based industries among Indigenous people in the monsoonal tropics of the Northern Territory and Professor Stephen Garnett (CDU) has broad experience in management of tropical environments, particularly northern Australia.\n
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".