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Record W2941123231 · doi:10.1177/1556264619835707

Decades of Doing: Indigenous Women Academics Reflect on the Practices of Community-Based Health Research

2019· article· en· W2941123231 on OpenAlexafffund
Kim Anderson, Jaime Cidro

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of WinnipegUniversity of Guelph
FundersUniversity of Winnipeg
KeywordsIndigenousResearch ethicsNegotiationSociologyPossession (linguistics)Work (physics)Community-based participatory researchPublic relationsPolitical scienceEngineering ethicsSocial scienceParticipatory action researchAnthropology

Abstract

fetched live from OpenAlex

It has been several decades since the establishment of Ownership, Control, Access, and Possession (OCAP®) and the proliferation of work on Indigenous research ethics. Most of this dialogue emerged because of egregious health research practices in Indigenous communities and has since taken a foothold across all disciplines. Community-engaged research in Indigenous communities is challenging. It is important to reflect on some of the early ethical and methodological debates, which shape how we currently work with communities. This research describes the themes that emerged when two Indigenous scholars interviewed their Indigenous university-based colleagues who work in Indigenous health. These interviews uncovered four critical themes that were prominent and related specifically to understanding research ethics in Indigenous health research specifically. These themes included research in relationship, creating partnerships and negotiating across systems, self-determination applied to research, and community-engaged research.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchScience and technology studies
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearchScience and technology studies
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.418
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4180.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0220.006
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0010.039
Insufficient payload (model declined to judge)0.0000.000

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 head0.825
GPT teacher head0.705
Teacher spread0.120 · 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

Labeled directly by 2 models reading the full record.

Study designQualitative
DomainMethods
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

Citations25
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Empirical Research on Human Research EthicsSame topicIndigenous Health, Education, and RightsCategoryMetaresearchFrench-language works237,207