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Record W99396412 · doi:10.1123/jsm.19.4.367

Putting “Participatory” into Participatory Forms of Action Research

2005· article· en· W99396412 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

VenueJournal of Sport Management · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of ReginaSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsParticipatory action researchCitizen journalismVariety (cybernetics)Action researchRelevance (law)SociologyAction (physics)Community-based participatory researchProcess (computing)Public relationsPopulationPolitical scienceComputer sciencePedagogy

Abstract

fetched live from OpenAlex

Although there has been a rise in calls for participatory forms of research, there is little literature on the challenges of involving research participants in all phases of the research process. Actively involving research participants requires new strategies, new researcher and research-participant roles, and consideration of a number of ethical dilemmas. We analyzed the strategies employed and challenges encountered based on our experiences conducting feminist participatory action research with a marginalized population and a variety of community partners over 3 years. Five phases of the research process were considered including developing the research questions, building trust, collecting data, analyzing data, and communicating the results for action. Our goals were to demonstrate the relevance of a participatory approach to sport management research, while at the same time acknowledging some of the realities of engaging in this type of research.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.290
GPT teacher head0.494
Teacher spread0.204 · 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