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Record W28474454 · doi:10.1080/713659422

Recognition, rights and resources: negotiating mining agreements on Indigenous lands in Canada and Australia

2013· article· en· W28474454 on OpenAlexaboutno aff
Margaret A. Stephenson

Bibliographic record

VenueDrug and Alcohol Review · 2013
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousNegotiationContext (archaeology)JurisprudenceGovernment (linguistics)Indigenous rightsPolitical scienceResource (disambiguation)DutyProperty rightsLand rightsBusinessEnvironmental resource managementLawEnvironmental planningGeographyHuman rightsEconomicsArchaeologyComputer science

Abstract

fetched live from OpenAlex

While the concepts of Aboriginal title share a similar jurisprudence in both Australia and Canada resource development regimes on Aboriginal title lands differ significantly. In Australia, the process is the right to negotiate with mining proponents. In Canada, the process is the duty to consult with government regarding mining projects. This paper compares and assesses the processes for ‘consultation and negotiation’ with Indigenous peoples when development actions (particularly in the context of mining resource development)impact Indigenous property rights and how agreement making can be progressed. This paper will question whether the resource development processes afford Indigenous people’s property rights full respect when mining developments on Indigenous lands are proposed.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.038
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.223
Teacher spread0.202 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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