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Record W7081963517 · doi:10.36487/acg_repo/2515_42

Argyle diamond mine: a model for First Nations engagement

2025· article· en· W7081963517 on OpenAlexaboutno aff

Bibliographic record

VenueMine closure · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsClosure (psychology)NegotiationWork (physics)Plan (archaeology)Best practiceMining industryProductivity

Abstract

fetched live from OpenAlex

The Gelganyem Group represents the Traditional Owners (TOs) of Argyle diamond mine in the remote East Kimberley region of North Western Australia. In November 2020 mining ceased at Argyle after 37 years of operations and the production of more than 865 million carats of rough diamonds. Just as Argyle’s TOs pioneered new ways to engage during exploration and mining, they have now designed a robust engagement strategy to lead the charge for the negotiation of positive technical, environmental, economic and cultural outcomes for all parties in mine closure. Whilst most mining companies appreciate the critical need to engage with First Nations groups to agree a closure vision and strategy, many do not know how best to do this. Gelganyem’s closure work plan (CWP) model: There are many lessons to be learned from the Argyle closure; the first mine closure of its size globally. First Nations participation in mine closure is critical to ensure its success. The CWP model will help mining companies and First Nations people work together to improve mine closure outcomes for everyone. Argyle TOs are keen to ensure that mining companies and other First Nations groups benefit from the Argyle experience and maximise positive, meaningful and effective First Nations engagement and participation in mine closure planning, design and execution.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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