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Record W2606192837 · doi:10.1017/s0008423917000257

Taking the Field: 50 Years of Indigenous Politics in the<i>CJPS</i>

2017· article· en· W2606192837 on OpenAlexaffabout
Kiera L. Ladner

Bibliographic record

VenueCanadian Journal of Political Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Science Research and Education
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousPoliticsWestphalian sovereigntyState (computer science)Political scienceField (mathematics)Focus (optics)Environmental ethicsSocial scienceSociologyLawSovereignty

Abstract

fetched live from OpenAlex

Abstract This article reviews the place of Indigenous politics in the last 50 years of Canadian political science. Focusing on the CJPS , it looks at broad themes and clusters in the literature over time, while also trying to explain how the roots of the discipline continue to impact the development of political science in Canada and thus CJPS . I argue that while at least 43 articles have dealt with Indigenous politics (solely or as a significant focus) and at least 18 have had some significant discussion thereof, there nonetheless remains a disconnect between Indigenous politics and the discipline. This disconnect exists because of the methodological and epistemological foundations of the discipline which have resulted in a focus limited to the Westphalian state. While the disconnect between Indigenous politics and the discipline has waned considerably (43 of 61 articles have been published since 2000) as there has been an awakening of sorts, a disconnect nevertheless still exists.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.020
Science and technology studies0.0130.018
Scholarly communication0.0160.006
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.055
GPT teacher head0.416
Teacher spread0.361 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
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

Citations35
Published2017
Admission routes2
Has abstractyes

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