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Record W1975266931 · doi:10.5130/ijcre.v3i0.1039

Participatory action research approaches and methods

2010· article· en· W1975266931 on OpenAlexaff
Nancy Gibson

Bibliographic record

VenueGateways International Journal of Community Research and Engagement · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsCanadian Institute for Energy Training
Fundersnot available
KeywordsParticipatory action researchAction (physics)Citizen journalismAction researchSection (typography)Process (computing)SociologyEngineering ethicsEpistemologyComputer scienceEngineeringAnthropologyPedagogyWorld Wide WebPhilosophy

Abstract

fetched live from OpenAlex

This book, published as part of Routledge’s Studies in Human Geography, is useful well beyond this discipline, as it provides a welcome review of Participatory Action Research (PAR). In three major sections, beginning and ending with ‘Reflections’ that bracket the ‘Action’ section, this collection provides a timely overview of the current status of this methodology, as well as many useful examples of applying PAR as a research process.

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)0.106
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.106
Threshold uncertainty score0.558

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1060.058
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.009
Science and technology studies0.0070.018
Scholarly communication0.0130.008
Open science0.0060.013
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0170.005

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 head0.962
GPT teacher head0.770
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations17
Published2010
Admission routes1
Has abstractyes

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