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Record W2048563127 · doi:10.1177/1476750306070104

Participatory action research

2006· article· en· W2048563127 on OpenAlexaff
Judy Burgess

Bibliographic record

VenueAction Research · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsParticipatory action researchReflexivityGeneral partnershipAction researchSociologyAction (physics)InsiderEpistemologyPower (physics)Citizen journalismProcess (computing)PraxisPolitical scienceSocial sciencePedagogyComputer science

Abstract

fetched live from OpenAlex

This article examines the tensions and challenges of a graduate student maneuvering the institutional hierarchies in her journey of participatory action research (PAR). By using a first-person action research framework, the researcher moves back and forth exploring the prose of others, and revealing her reflexive self-inquiry of underlying assumptions and beliefs. Iterations of insider-outsider positionality, drawing on and integrating paradigms, reconciling multiple roles and perspectives, exploring the complexity of power relations, and uncovering the promises and perils of PAR, moves the researcher toward a partnership with her community of inquiry. First-person action research unfolds a process of self-transformation.

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)0.098
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.098
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.079
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0120.014
Scholarly communication0.0090.006
Open science0.0040.016
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0240.005

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 head0.981
GPT teacher head0.832
Teacher spread0.148 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations170
Published2006
Admission routes1
Has abstractyes

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