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Record W3006688704 · doi:10.18584/iipj.2020.11.1.10237

Advancing Indigenous Research Sovereignty: Public Administration Trends and the Opportunity for Meaningful Conversations in Canadian Research Governance

2020· article· en· W3006688704 on OpenAlexaffvenueabout
Keith Williams, Umar Umangay, Suzanne Brant

Bibliographic record

VenueInternational Indigenous Policy Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsIndigenousSovereigntyPublic administrationCorporate governancePolitical scienceColonialismSociologyLawPoliticsManagement

Abstract

fetched live from OpenAlex

Federally funded research in Canada is of significant scope and scale. The implications of research in the colonial project has resulted in a fraught relationship between Indigenous Peoples and Western research. Research governance, as an aspect of public administration, is evolving. The relationality inherent in new public governance (NPG)—a nascent public governance regime—may align with Indigenous relationality concepts. Recent societal advances, such as the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), the Truth and Reconcilliation Commission of Canada (TRC), and the Indigenous Institutes Act in Ontario, provide further impetus for Indigenous self-determination in multiple domains including research. This article advocates for Indigenous research sovereignty and concludes with suggestions for ways in which federal funding agencies, specifically the Social Sciences and Humanities Research Council (SSHRC), could contribute to the advancement of Indigenous research sovereignty.

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)0.107
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1070.090
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0610.067
Scholarly communication0.0330.018
Open science0.0050.020
Research integrity0.0080.019
Insufficient payload (model declined to judge)0.0060.000

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 head0.156
GPT teacher head0.456
Teacher spread0.300 · 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 designQualitative
DomainIncentives
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

Citations17
Published2020
Admission routes3
Has abstractyes

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