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Record W2924611539 · doi:10.4324/9781315730639-6

Self-determination and indigenous governance in the Arctic

2018· book-chapter· en· W2924611539 on OpenAlexaboutno aff
Mark Nuttall

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousArcticCorporate governanceThe arcticSelf-governanceGeographyEnvironmental scienceOceanographyBusinessEcologyGeologyBiologyFinance

Abstract

fetched live from OpenAlex

This chapter describes social, economic and environmental changes affect Arctic environments, wildlife, and communities in profound ways. Some Arctic states have recognized the need to settle some of the claims indigenous peoples advance for land and self-government, or have sought to pass legislation that recognizes the need for dialogue on land claims and resource rights. The arrangements where indigenous peoples have the greatest autonomy are to be found in the models of tribal sovereignty/self-government and land claims in Alaska, in comprehensive land claims agreements in Canada, and in the system of extensive self-government in Greenland. Greenland has often been considered a model for indigenous self-government, but it has been a process of nation-building rather than an ethno-political movement. Indigenous homelands, people&s;s livelihoods and traditional resource use in the Arctic are also being challenged today, however, by environmental change such as witnessed in the effects of climate variability and a rapidly warming Arctic.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.006
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.288
Teacher spread0.267 · 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
GenreOther

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

Citations8
Published2018
Admission routes1
Has abstractyes

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Same topicArctic and Russian Policy StudiesFrench-language works237,207