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Record W4200465715 · doi:10.18037/ausbd.1039507

Indigenous People as Self-Narratives of Canada For Building Ontological Security in the Arctic

2021· article· en· W4200465715 on OpenAlexaboutno aff
Adnan DAL

Bibliographic record

VenueAnadolu Üniversitesi Sosyal Bilimler Dergisi · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOntological securityIndigenousArcticNarrativeIdentity (music)State (computer science)Security studiesPolitical scienceSelf-determinationNational securitySociologyPublic administrationLawComputer scienceAestheticsEcology

Abstract

fetched live from OpenAlex

The understanding of traditional security is undergoing a more multi-faceted transformation. Security itself is no more regarded as being limited to a physical presence, it requires a stable self as well. Claiming this, ontological security theory enables scholars to examine state behavior which strengthens identity values via self-narratives. This study aims to reveal that the traditional security perception of Canadian governments is limited in evaluating their relations with the Arctic states and indigenous people, therefore, in recent years, the relevant governments have provided Canadian ontological security in the Arctic region by constructing indigenous people as self-narratives. Therefore, in this paper, instead of traditional national security, it is mentioned that ontological security theory better articulates the state behavior of Canada both domestically and internationally. In the study, the qualified document analysis method is used by examining the reports that include the indigenous peoples as a significant part of Canada's national identity and the declarations announced at the ministerial meetings of the Arctic Council after the chairmanship of Canada. In this way, the study concludes by mentioning that Canada has built its ontological security by constructing self-narratives from indigenous peoples to have a robust position in the 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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