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Record W2346803537 · doi:10.1177/1476750315572447

Moving with the movement: Collaboratively building a participatory action research study of social movement learning in Ada, Ghana

2015· article· en· W2346803537 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAction Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSt. Francis Xavier University
FundersSt. Francis Xavier UniversityWorld Bank Group
KeywordsParticipatory action researchMovement (music)Social movementCitizen journalismAction researchProcess (computing)Action (physics)Social learningSociologyDemocracySocial movement theoryPublic relationsPolitical sciencePedagogyComputer sciencePolitics

Abstract

fetched live from OpenAlex

While participatory research methods, especially participatory action research, are a recognized approach to the study of social movement learning, the way in which this participatory relationship is framed and designed has deep implications on the collaborative nature of the research. Studies overly framed and designed by academics, as opposed to collectively designed with movements, run the risk of mining movements for information as opposed to contributing to their goals and learning. This paper describes a co-owned design process, based on established relationships, with a social movement in Ghana where being based in movement-articulations helps the research move with the movement. This co-owned process sets the stage for the emergence of movement embedded knowledge democracy.

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)0.073
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0730.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.874
GPT teacher head0.715
Teacher spread0.158 · 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