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Record W4313441314 · doi:10.18584/iipj.2022.13.3.13961

"A serious rift": The Indigenous Health Research Community's Refusal of the 2014 CIHR Funding Reforms and Underlying Methodological Conservatism

2022· article· en· W4313441314 on OpenAlexafffundvenueabout
John Rose, Heather Castleden

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of VictoriaQueen's University
FundersMedical Research CouncilCanadian Institutes of Health ResearchGovernment of CanadaNational Institutes of HealthNational Health and Medical Research CouncilQueen's UniversityCanada Research Chairs
KeywordsIndigenousConservatismPolitical sciencePsychological interventionPublic relationsPublic administrationSociologyMedicineLawNursingPolitics

Abstract

fetched live from OpenAlex

In 2014, the Canadian Institutes of Health Research (CIHR) senior administration established reforms to the Open Suite of Programs and Peer Review processes (OSP), implementing changes that it claimed would improve its funding and peer review structures. The purpose of the research reported in this paper was to investigate how CIHR reforms to the OSP were poised to negatively affect Indigenous health research. We found that the reforms were guided by a governmental and institutional trajectory of methodological conservatism that (a) privileged commercial research over projects that focus on social determinants of health and community relations, and (b) created a peer review system re-designed in ways that reduce inclusiveness. Interventions by the CIHR Institute of Indigenous Peoples Health' Advisory Board and an ad-hoc Indigenous Health Research Steering Committee (kahwa:tsire) were urgently organized and mobilized to reverse the CIHR decisions that were being made under the guise of so-called 'consultation.’

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)0.551
metaresearch head score (Gemma)0.536
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.553

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5510.536
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0320.071
Scholarly communication0.0310.015
Open science0.0080.020
Research integrity0.0210.048
Insufficient payload (model declined to judge)0.0020.000

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 head0.392
GPT teacher head0.525
Teacher spread0.133 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations1
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueInternational Indigenous Policy JournalSame topicIndigenous Health, Education, and RightsFrench-language works237,207