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Record W4387704592 · doi:10.1080/10357718.2023.2268030

Faces of ‘not knowing’ in International Relations

2023· article· en· W4387704592 on OpenAlexaff
J. Marshall Beier

Bibliographic record

VenueAustralian Journal Of International Affairs · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIndigenousInternational relationsSovereigntyAutonomyPolitical scienceInternational relations theoryPower (physics)SociologyPoliticsIndigenous rightsHegemonyGlobal governanceEnvironmental ethicsLawPolitical economyEpistemology

Abstract

fetched live from OpenAlex

That Indigenous diplomacies remain largely unknown to states and to disciplinary International Relations is, ultimately, a matter of choices made by those privileged in terms of the power to (re)produce social facts and common senses. Distinguishing distinct faces of ‘not knowing’ exposes ontological commitments underwriting the logics of territorially exclusive sovereign power and the knowledge practices of International Relations that, in both spheres, make Indigenous ways of knowing and being in the world seem implausible. ‘Not knowing’ in this sense is a form of rejection of knowledge and, therefore, a consequential practice which, as such, is never politically innocent. Relational autonomy raises a challenge to the rigid singularism and exclusivity of dominant ontologies—one that is rooted in long-run historical experiences of still-existing Indigenous forms of community and inter-national diplomatic practice. Among other things, it points us to more sustainable possibilities upon which to found relations between polities and reminds us that diplomacies are always plural.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.351
Teacher spread0.317 · 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 designNot applicable
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

Citations3
Published2023
Admission routes1
Has abstractyes

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