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Record W2904584314 · doi:10.1080/22423982.2018.1556558

Research governance in NunatuKavut: engagement, expectations and evolution

2018· article· en· W2904584314 on OpenAlexaffabout
Julie Bull, Amy Hudson

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsIndigenousResearch ethicsCorporate governanceCommunity engagementPolitical scienceInformed consentCommunity-based participatory researchSociologyEnvironmental ethicsPublic relationsGeographyEngineering ethicsParticipatory action researchEcologyAnthropologyMedicineManagementEngineeringBiology

Abstract

fetched live from OpenAlex

Some of the world's most southern Inuit populations live along central and the southeastern coast of Labrador in the territory of NunatuKavut and are represented by the NunatuKavut Community Council (NCC). Southern Inuit and NCC staff have been actively collaborating with researchers and research ethics boards since 2006 on research ethics and the governance of research in NunatuKavut. As self-determining peoples, Southern Inuit, like many Indigenous communities, are reclaiming control of research through a number of highly effective community consent contracts and ethical review processes and protocols. These community-driven research agreements have both shaped, and been shaped by, academic writings on the issue of collective consent to research. This case report describes the evolution of NCC research governance from 2006 to 2018, emphasising the ethics and engagement that is required to conduct research with Southern Inuit or within the territory of NunatuKavut.

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)0.027
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0200.021
Scholarly communication0.0130.006
Open science0.0020.013
Research integrity0.0020.003
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 head0.095
GPT teacher head0.504
Teacher spread0.409 · 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
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

Citations10
Published2018
Admission routes2
Has abstractyes

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