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Record W2167083241 · doi:10.1525/jer.2010.5.4.23

Researchers' Perspectives on Collective/Community Co-Authorship in Community-Based Participatory Indigenous Research

2010· article· en· W2167083241 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2010
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsIndigenousCommunity-based participatory researchParticipatory action researchCitizen journalismThematic analysisSociologyPublic relationsValue (mathematics)Qualitative researchPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Ethical tensions exist regarding the value and practice of acknowledging Indigenous contributions in community-based participatory research (CBPR). Semistructured phone interviews with researchers documented their perspectives on authorship in the scholarly dissemination of their community-based participatory Indigenous research. Thematic analysis resulted in four key ideas: (1) current practices regarding methods of acknowledging community contributions; (2) requirements for shared authorship with individual versus collective/community partners; (3) benefits to sharing authorship with collective/community partners; and (4) risks to sharing authorship with collective/community partners. Findings suggest an emerging but inconsistent practice.

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.

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
gemmaMetaresearchResearch integrity
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
gptResearch integrityScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models splitAgreement 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)0.506
metaresearch head score (Gemma)0.096
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5060.096
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.006
Science and technology studies0.0280.006
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0020.249
Insufficient payload (model declined to judge)0.0010.001

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 head0.972
GPT teacher head0.777
Teacher spread0.196 · 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