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Record W1605086767 · doi:10.20355/c5pk58

Is Participatory Action Research Relevant in the Canadian Workplace?

2010· article· en· W1605086767 on OpenAlexaffvenueabout
Candy Khan, Donna M. Chovanec

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrassrootsEmpowermentAction (physics)Participatory action researchCitizen journalismSociologyPower (physics)Political scienceEpistemologyEngineering ethicsSocial scienceEngineeringLawPolitics

Abstract

fetched live from OpenAlex

Participatory Action Research (PAR), with its emphasis on grassroots empowerment and local control, has a long history as the research method of choice for marginalized communities. However, unsettling questions remain about the nature of power and the promise of PAR as a truly participatory and empowering methodology. In this paper, we summarize the key theorists, principles, methodology, researcher’s role, strengths and limitations of traditional PAR. In the subsequent section, we review current critiques and revisions of PAR. Finally, Khan proposes an adjustment to PAR that reflects the strengths and limitations of PAR and the implications of applying PAR within the bounds of a capitalist social-economic structure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.061
metaresearch head score (Gemma)0.111
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.999

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.111
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.013
Science and technology studies0.0390.050
Scholarly communication0.0300.012
Open science0.0050.010
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.749
GPT teacher head0.702
Teacher spread0.047 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
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

Citations32
Published2010
Admission routes3
Has abstractyes

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