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Record W2614114933 · doi:10.1111/emr.12257

The Uunguu Monitoring and Evaluation Committee: Intercultural Governance of a Land and Sea Management Programme in the Kimberley, Australia

2017· article· en· W2614114933 on OpenAlexaff
Beau J. Austin, Tom Vigilante, S. Cowell, Ian Dutton, Dorothy Djanghara, Scholastica Mangolomara, Bernard Puermora, Albert Bundamurra, Zerika Clement

Bibliographic record

VenueEcological Management & Restoration · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsImpactNautilus Environmental
FundersAustralian Research Council
KeywordsIndigenousThreatened speciesEnvironmental resource managementAdaptive managementTraditional knowledgeBiodiversityCorporate governanceEnvironmental planningLand managementMonitoring and evaluationGeographyLand useEcologyPolitical scienceBusinessBiology

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.138
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.729

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1380.115
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.126
GPT teacher head0.429
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2017
Admission routes1
Has abstractyes

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