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Record W2098275303 · doi:10.14430/arctic315

Investigating Local Definitions of Sustainability in the Arctic: Insights from Post-Soviet Sakha Villages

2009· article· en· W2098275303 on OpenAlexvenueno aff
Susan A. Crate

Bibliographic record

VenueARCTIC · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCircumpolar starSustainabilityIndigenousArcticTraditional knowledgeGlobalizationPolitical scienceGeographyResource (disambiguation)Local communityEnvironmental resource managementSociologyEcology

Abstract

fetched live from OpenAlex

Contemporary survival for post-Soviet Russia’s indigenous communities is complicated both by a Soviet legacy that undermined local ecological knowledge, kinship settlement patterns, land and resource rights, and robust ecosystems, and by the contemporary effects of globalization and modernity. Efforts to achieve sustainability lack a focus on local contexts, although recent research, especially in anthropology, underscores the need to develop sustainability criteria that are both flexible and adaptable to local contexts. Community-based research in post-Soviet Viliui Sakha indigenous communities of northeastern Siberia, Russia, has shown that inhabitants define sustainability as the building of local diversified economies, communities, and health via strong local leadership, a shared vision to work toward common goals, the reinstatement of local knowledge, and rights to land and resources. Realization of these ideas may be achieved by continued collaboration between circumpolar researchers and communities to facilitate the influx of ideas and models of success from other Arctic regions and by potential outcomes of intergovernmental action between the Russian Federation and its circumpolar neighbors through Russia’s chairing of the Arctic Council. Implementation of flexible, locally adaptable sustainability criteria is central to these efforts.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.345
Teacher spread0.303 · 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 designObservational
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

Citations25
Published2009
Admission routes1
Has abstractyes

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