MétaCan
Menu
Back to cohort
Record W4324128541 · doi:10.1080/14461242.2023.2173017

<i>Debakarn Koorliny Wangkiny</i> : steady walking and talking using first nations-led participatory action research methodologies to build relationships

2023· article· en· W4324128541 on OpenAlexaboutno aff
Michael Wright, Tiana Culbong, Michelle Webb, Amanda Sibosado, Tanya Jones, Tilsa Guima Chinen, Margaret O’Connell

Bibliographic record

VenueHealth Sociology Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilHealthway
KeywordsParticipatory action researchMainstreamSociologyScholarshipCitizen journalismAction researchPublic relationsProject commissioningPublishingPolitical sciencePedagogyLawAnthropology

Abstract

fetched live from OpenAlex

Aboriginal participatory action research (APAR) has an ethical focus that corrects the imbalances of colonisation through participation and shared decision-making to position people, place, and intention at the centre of research. APAR supports researchers to respond to the community's local rhythms and culture. APAR supports researchers to respond to the community's local rhythms and culture. First Nations scholars and their allies do this in a way that decolonises mainstream approaches in research to disrupt its cherished ideals and endeavours. How these knowledges are co-created and translated is also critically scrutinised. We are a team of intercultural researchers working with community and mainstream health service providers to improve service access, responsiveness, and Aboriginal client outcomes. Our article begins with an overview of the APAR literature and pays homage to the decolonising scholarship that champions Aboriginal ways of knowing, being, and doing. We present a research program where Aboriginal Elders, as cultural guides, hold the research through storying and cultural experiences that have deepened relationships between services and the local Aboriginal community. We conclude with implications of a community-led engagement framework underpinned by a relational methodology that reflects the nuances of knowledge translation through a co-creation of new knowledge and knowledge exchange.

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)0.035
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0260.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.566
GPT teacher head0.571
Teacher spread0.004 · 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 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

Citations23
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHealth Sociology ReviewSame topicIndigenous Health, Education, and RightsFrench-language works237,207