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Record W3025406951 · doi:10.1002/sd.2063

From pay‐out to participation: Indigenous mining employment as local development?

2020· article· en· W3025406951 on OpenAlexaboutno aff
Sarah Holcombe, Deanna Kemp

Bibliographic record

VenueSustainable Development · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
FundersUniversity of Queensland
KeywordsIndigenousNegotiationContext (archaeology)LegitimacyEquity (law)State (computer science)Political scienceCorporate governanceEconomic growthEconomicsGeographyLawManagement

Abstract

fetched live from OpenAlex

Abstract Unprecedented numbers of Indigenous peoples in Canada and Australia are working in the mining industry. This study explores the proposition that Indigenous mining employment is a form of local development for these peoples. We establish links between the literatures on Indigenous work in the mining industry with development theory. For employment to be considered a form of local development we maintain that it must be understood through the framework of self‐determination, as this applies within a colonial context. A range of potentially enabling requirements is identified, including effective regional governance, career progression, gender equity and equality, and free prior and informed consent. We argue that, where such conditions are not in place, Indigenous peoples in settler states, such as Australia and Canada, risk swapping one kind of dependency for another: the welfare state for the mining economy. It is important that future research test the legitimacy of these conditions, while exploring alternative value propositions when mining companies seek to negotiate access to Indigenous peoples land and resources.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.018
Scholarly communication0.0080.004
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.000

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 head0.015
GPT teacher head0.228
Teacher spread0.214 · 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

Citations45
Published2020
Admission routes1
Has abstractyes

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