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Record W7117224372

Indigenous Peoples, Natural Resources and Governance

2022· article· en· W7117224372 on OpenAlexaboutno aff
Tennberg M., Broderstad E. G.

Bibliographic record

VenueRepository of Samara University (Samara National Research University) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousNatural resourceCorporate governanceMultidisciplinary approachPoliticsGlobalizationArcticIndigenous rightsResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

This book offers multidisciplinary perspectives on the changing relationships between states, indigenous peoples and industries in the Arctic and beyond. It offers insights from Nordic countries, Canada, Australia, New Zealand and Russia to present different systems of resource governance and practices of managing industry-indigenous peoples'relations in the mining industry, renewable resource development and aquaculture. Chapters cover growing international interest on Arctic natural resources, globalization of extractive industries and increasing land use conflicts. It considers issues such as equity, use of knowledge, development of company practices, conflict-solving measures and the role of indigenous institutions. Focus on Indigenous peoples and Governance triangle Multidisciplinary: political science, legal studies, sociology, administrative studies, Indigenous studies Global approach: Nordic countries, Canada, Russia, Australia, New Zealand and Canada Thorough case studies, rich material and analysis

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.167
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.014
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.031
GPT teacher head0.292
Teacher spread0.261 · 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 designNot applicable
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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