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Record W2277007158

Arctic Energy Development and Best Practices on Consultation with Indigenous Peoples

2013· article· en· W2277007158 on OpenAlexaff
Dwight Newman, Michelle Biddulph, Lorelle Binnion

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousArcticThe arcticBest practicePolitical scienceSustainable developmentEnergy (signal processing)Environmental planningEnvironmental resource managementGeographyEconomic growthPublic relationsLawEnvironmental scienceEconomicsEcologyOceanography
DOInot available

Abstract

fetched live from OpenAlex

Arctic energy development has massive potential in helping meet world energy needs and in promoting sustainable Arctic development. At the same time, the Arctic is largely inhabited by Indigenous peoples and has special environmental vulnerabilities that can contribute to impacts on Arctic Indigenous peoples. Norms of consultation with Indigenous peoples thus have a particular importance in Arctic contexts. This Article examines this very much under-studied issue. It seeks to make an innovative contribution to understanding best practices on consultation appropriate to Arctic-specific contexts, considering evolving national and international law norms of consultation. Part II of the Article carries out a comparison of existing implementations of international norms of consultation in countries across the Arctic region. Part III distills best practices on consultation from both evolving national and international law, including both in the Arctic states but also in other states whose practices can shed light. Part IV examines unique Arctic circumstances and develops a set of categories for Arctic-specific consideration of consultation. Part V ties together the best practices and the impact categories of Part IV and seeks to comment on the existing state practices discussed in Part II, signalling directions in which different states might consider shifting so as to best respect consultation norms. The underlying aim of the Article is to offer practical recommendations that facilitate Arctic energy development in responsible ways, thereby furthering its long-term acceptability and potential.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.289
Teacher spread0.271 · 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 teacher head, not a consensus.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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