The Uunguu Monitoring and Evaluation Committee: Intercultural Governance of a Land and Sea Management Programme in the Kimberley, Australia
Bibliographic record
Abstract
Summary The importance of Indigenous peoples’ and their ancestral estates for the maintenance and protection of biodiversity, ecosystem function, threatened species and cultural diversity is clear. Due to their nature, processes and tools to measure the impact of intercultural Indigenous land and sea management partnerships need to be innovative and adaptable. In 2015, the Wunambal Gaambera Healthy Country Plan reached its mid‐point, which triggered an evaluation to enable adaptive management through the assessment of effectiveness. The evaluation was used to appraise the need for adaptation, contribute to the evidence base for healthy Country, and to report on achievements. The Uunguu Monitoring and Evaluation Committee, an innovative, intercultural and interdisciplinary body, and their collaborators adopted a multiple evidence‐based approach to enable an enriched picture. This committee has successfully integrated western scientific and local Indigenous knowledge for adaptive management by embodying the principles of co‐production. The Uunguu Monitoring and Evaluation Committee model outlines a way of doing knowledge integration from the bottom up which, given the significance of the cultural and natural diversity of the Indigenous estate, makes a valuable contribution to the global community of practitioners attempting to use diverse knowledges for better management of biodiversity, ecosystems, threatened species and cultural traditions.
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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 | 0.138 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".