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Record W4410638083 · doi:10.1139/facets-2024-0114

The evolution of local engagement and the mode of knowledge production in Arctic research: 2011–2020

2025· article· en· W4410638083 on OpenAlexafffundvenue
Nicolas D. Brunet, Quinn E. Fletcher

Bibliographic record

VenueFACETS · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of Guelph
FundersGovernment of CanadaUniversity of Guelph
KeywordsProduction (economics)Mode (computer interface)Knowledge productionArcticKnowledge managementEnvironmental resource managementEnvironmental scienceGeographyOceanographyComputer scienceHuman–computer interactionGeologyEconomics

Abstract

fetched live from OpenAlex

Community-based approaches have received considerable attention in Arctic research discourse over the last couple of decades with some claims of a new research paradigm taking shape within this region. Here, we sought to empirically test if Arctic research has been transformed by an increased involvement of local people in the 10 years following the end of the time period examined in Brunet et al. (N.D. Brunet, G.M. Hickey, and M.M. Humphries. 2014. The evolution of local participation and the mode of knowledge production in Arctic research. Ecology and Society, 19(2): 69. doi:10.5751/ ES-06641-190269), where trends from 1965 to 2010 were explored. We used a quantitative assessment framework to conduct an analysis of all research articles appearing between 2011 and 2020 in the journal Arctic. We found no significant changes in local engagement over this time period nor clear indications of a paradigm shift, despite policy changes supporting self-determination in research in some jurisdictions. We found that, in general, trends from the 2014 study held true for the 2011–2020 time period with a few minor distinctions. We discuss key themes that have emerged from this study, namely some promising authorship trends, the continued role of certain disciplines in leading the push towards meaningful local engagement and the contributions of climate change research to local leadership in research.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.068
GPT teacher head0.401
Teacher spread0.333 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2025
Admission routes3
Has abstractyes

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