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Record W3132898394 · doi:10.32799/ijih.v16i2.33099

Bringing Ethics Review Home to Cowichan: Indigenizing Ethics Review in British Columbia, Canada

2021· article· en· W3132898394 on OpenAlexfundvenueaboutno aff
Cowichan Tribes

Bibliographic record

VenueInternational Journal of Indigenous Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
FundersVancouver Foundation
KeywordsIndigenousGeneral partnershipPossession (linguistics)CommissionDeclarationResearch ethicsFirst nationPolitical scienceLawPublic administrationSociologyEcologyEngineeringEngineering ethics

Abstract

fetched live from OpenAlex

Cowichan Tribes’ territory, located in the Cowichan Valley on Vancouver Island, British Columbia, Canada, is experiencing an alarmingly high rate of preterm births compared to the national average of Indigenous Peoples in Canada. In response, and in partnership with the First Nations Health Authority (FNHA), Cowichan Tribes is in the first year of a 3-year study to investigate causes. Cowichan Tribes’ Elders and community members are guiding the study to ensure it follows Cowichan Tribes’ research processes and to support self- determination in research. Furthermore, as a way to enhance reconciliation, Elders and community members guided an on-site ethics review on Cowichan Tribes territory. This article outlines the collaborative, in-person research ethics review process that Cowichan Tribes, Island Health, and FNHA completed on August 21, 2019. The purpose of this article is to provide suggestions other First Nations could use when conducting a research ethics review, and to explain how this process aligns with the principles of ownership, control, access, and possession (OCAP®), the United Nations Declaration on the Rights of Indigenous Peoples, the Truth and Reconciliation Commission of Canada, and above all, the Cowichan snuw’uy’ulh (teachings from Elders).

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)0.041
metaresearch head score (Gemma)0.064
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.021
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 head0.107
GPT teacher head0.504
Teacher spread0.396 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2021
Admission routes3
Has abstractyes

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