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Record W2093609145 · doi:10.1068/a3996

‘Choosing’ Participatory Research: Partnerships in Space–Time

2007· article· en· W2093609145 on OpenAlexaffabout
Fran Klodawsky

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsParticipatory action researchAction (physics)Citizen journalismContext (archaeology)SociologyAction researchPoliticsSpace (punctuation)Public relationsEngineering ethicsPolitical scienceEpistemologyLawEngineeringComputer sciencePedagogyGeography

Abstract

fetched live from OpenAlex

Participatory action research has increasing attention in geography in recent years, with numerous discussions about how best to proceed and lessons learned from past efforts. There has been less interest, though, in critically probing the circumstances under which participatory research takes place: in other words, the sociospatial contexts within which such research approaches are chosen. One explanation may be that participatory action researchers sometimes infer that the reasons for their choices are primarily ethical and political. In this paper, I consider this and other assumptions about participatory action research, drawing upon my own involvement in two action research projects in Ottawa, Canada. I argue that reflecting on this question is a particularly timely undertaking, given the ‘actually existing neoliberalisms’ in which professionalization and partnerships are becoming more prominent. I begin by reviewing what has been said about participatory action research and the circumstances under which this approach is likely to be selected, and reflect on how these discussions might be enhanced by linking their circumstances specifically to emerging analyses about spaces of neoliberalism. Using these insights, I then examine the sociospatial context for the two studies and how their characteristics had specific effects on their methodological choices. All of these elements provide the scaffolding for consideration of the rationalities that supported the usage of participatory research in one study and the lack of engagement with this approach in the other.

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 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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.191
GPT teacher head0.341
Teacher spread0.150 · 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 teacher head, not a consensus.

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

Citations25
Published2007
Admission routes2
Has abstractyes

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