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Record W3088401953 · doi:10.1177/1049732320960050

Grounded in Culture: Reflections on Sitting Outside the Circle in Community-Based Research With Indigenous Men

2020· article· en· W3088401953 on OpenAlexafffund
Candice Waddell-Henowitch, Rachel Herron, Jason Gobeil, Frank Tacan, Margaret De Jager, Jonathan A. Allan, Kerstin Roger

Bibliographic record

VenueQualitative Health Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of ManitobaBrandon University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsParticipatory action researchIndigenousCommunity-based participatory researchSociologyReflexivityNegotiationQualitative researchPhotovoicePhoto elicitationGrounded theoryGender studiesPublic relationsSocial sciencePolitical scienceAnthropologyEconomic growth

Abstract

fetched live from OpenAlex

Research continues to be a dirty word for many Indigenous people. Community-based participatory research (CBPR) is a means to disrupt power dynamics by engaging community members within the research process. However, the majority of relationships between researcher and participants within CBPR are structured within Western research paradigms and they often reproduce imbalances of power. The purpose of this article is to reflect on the process of CBPR within a research project focused on Indigenous men's masculinity and mental health. In doing so, we aim to contribute to reflexive practice in CBPR and flatten research hierarchies to facilitate more equitable knowledge sharing. Our reflections highlight the importance of prioritizing healing, centering cultural protocols, negotiating language, and creating space for Indigenous research partners to lead. These critical lessons challenge Western researchers to ground their practices in Indigenous culture while they "sit outside the circle" to facilitate more equitable and engaged partnerships.

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)0.094
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0940.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0110.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.020
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 head0.899
GPT teacher head0.726
Teacher spread0.173 · 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 teacher head, 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

Citations12
Published2020
Admission routes2
Has abstractyes

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