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Record W4401072028 · doi:10.1080/14759551.2024.2383892

In choppy waters with a critical friend: the benefits of intimate reflexive encounters in participatory action research

2024· article· en· W4401072028 on OpenAlexafffund
Amrita Hari, Luciara Nardon

Bibliographic record

VenueCulture and Organization · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReflexivityAutoethnographySensemakingSociologyAction researchContext (archaeology)Action (physics)Participatory action researchActive listeningCitizen journalismEpistemologyPublic relationsSocial sciencePedagogyPolitical science

Abstract

fetched live from OpenAlex

We explore the benefits of intimate reflexive encounters with a ‘critical friend’ in the context of a Participatory Action Research (PAR) project. We conceptualize these encounters as an evolving relationship between a kayaker who supports the swim (research) and the swimmer (researcher). Methodologically, we adopt a form of co-constructed autoethnography and contribute to ongoing collective approaches to reflexivity and explorations in co-writing. We demonstrate how through asking clarifying questions, probing assumptions, listening to, and validating emotions, and orienting towards solutions, a ‘critical friend’ can support the researcher in engaging in reflexive sensemaking. Overall, these intimate encounters reveal assumptions, anxieties, challenges, limitations, and a range of emotions involved in conducting PAR. The kayaker and swimmer harness the power of peer support and create spaces of collegiality to resist the growing individualization and ever-increasing pressures of academic work.

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)0.081
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.427

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.135
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0280.055
Scholarly communication0.0210.024
Open science0.0040.035
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0070.002

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 head0.542
GPT teacher head0.646
Teacher spread0.104 · 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 designQualitative
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

Citations2
Published2024
Admission routes2
Has abstractyes

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