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Record W2579409847 · doi:10.1177/1476750316680722

What stories to tell? A trilogy of methods used for knowledge exchange in a community-based participatory research project

2017· article· en· W2579409847 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

VenueAction Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsParticipatory action researchAction researchTrilogyContext (archaeology)SociologyAction (physics)Citizen journalismIndigenousTraditional knowledgePublic relationsEngineering ethicsEpistemologyPolitical sciencePedagogyComputer scienceHistoryEngineeringWorld Wide WebEcology

Abstract

fetched live from OpenAlex

Researchers in the field of Aboriginal health generally have a keen interest in ‘participating in change’ to address the ongoing injustices experienced by Aboriginal peoples. Perhaps the most promoted methods for this purpose are those described as Indigenous methods and action research. Criteria of authenticity are generally used to assess the quality of research. In this essay, we reflect on how certain basic principles of action research, more notably ontological authenticity and educative authenticity can penetrate the process of knowledge exchange, creating spaces of ontological contamination and transformation. We reflect on the context of sharing ‘difficult knowledge’, knowledge that is encountered and shared in a post-colonial context of unequal power dynamics. We describe a trilogy of methods used for such knowledge exchange activities with three distinct audiences, and distinct goals. A commonality amongst the three described methods is the ‘unfinished’ and unorganised nature of what is transmitted, requiring the receptor to actively participate in the differentiation and reorganisation of information in a way that makes sense to him/her.

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)0.198
metaresearch head score (Gemma)0.083
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1980.083
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.002
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 head0.980
GPT teacher head0.830
Teacher spread0.150 · 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