Argyle diamond mine: a First Nations perspective on closure
Bibliographic record
Abstract
The Gelganyem Group represents the Traditional Owners 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 producing more than 865 million carats of rough diamonds. Just as Argyle Traditional Owners had to pioneer new ways of working with mining companies when asserting their rights during exploration, and negotiating land agreements during mining, they are now leading the charge for the negotiation of positive outcomes for First Nations people in mine closure. There are many lessons to be learnt from Argyle’s closure: the first mine closure of its size globally. Argyle Traditional Owners are keen to ensure that mining companies and other First Nations groups: learn from the Argyle experience start mining negotiations with closure in mind understand the critical importance of an agreed closure vision understand what effective engagement looks like work to understand the cultural differences in approach to closure and to the value of land work closely with industry and government to ensure mine closure requirements are fit-for-purpose maximise First Nations engagement and participation in mine site restoration use closure to tell the story of Aboriginal leadership, connection to Country, and resilience. First Nations participation in mine closure is critical to ensure its success. The lessons learnt from the closure of Argyle diamond mine will help mining companies and First Nations people work together to improve mine closure outcomes for everyone.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".