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Record W2151798429 · doi:10.1177/2333393615580764

Indigenous Storytelling and Participatory Action Research

2015· article· en· W2151798429 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.

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsParticipatory action researchIndigenousStorytellingTraditional knowledgeCitizen journalismRelation (database)ScholarshipNarrativeSociologyAction (physics)Political scienceEngineering ethicsAnthropologyEngineeringEcologyComputer scienceLaw

Abstract

fetched live from OpenAlex

Storytelling, in its various forms, has often been described as a practice with great emancipatory potential. In turn, Indigenous knowledge shows great promise in guiding a participatory action research (PAR) methodology. Yet these two approaches are rarely discussed in relation to one another, nor, has much been written in terms of how these two approaches may work synergistically toward a decolonizing research approach. In this article, I report on a community-driven knowledge translation activity, the Peoples' International Health Tribunal, as an exemplar of how narrative and PAR approaches, guided by local Indigenous knowledge, have great potential to build methodologically and ethically robust research processes. Implications for building globally relevant research alliances and scholarship are further discussed, particularly in relation to working with Indigenous communities.

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.

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)0.139
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1390.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.008
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.973
GPT teacher head0.832
Teacher spread0.141 · 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