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Record W2392284092 · doi:10.1177/1468794115619002

Queer de-participation: reframing the co-production of scholarly knowledge

2015· article· en· W2392284092 on OpenAlexaff
Alison L. Bain, W. J. Payne

Bibliographic record

VenueQualitative Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsYork University
Fundersnot available
KeywordsCognitive reframingQueerParticipatory action researchSociologyContext (archaeology)Power (physics)NarrativeCitizen journalismPoliticsAction researchGender studiesKnowledge productionUnpackingFeminismPublic relationsPolitical sciencePedagogyLawSocial psychologyPsychology

Abstract

fetched live from OpenAlex

This article critically examines the play of power in the co-production of scholarly knowledge in the context of a queer, feminist Participatory Action Research (PAR) project. By unpacking the power relations inherent in crafting a narrative of a collective project for a broader audience, we consider the conflicts, silences, and erasures that we experienced as participants, gatekeepers, and co-authors. We analyze iterations of a co-produced conference and journal article papers to recall the power dynamics that framed and reframed the outcomes of this project. In so doing, we critique what ‘co-’ and ‘with’ actually mean in the practice of publishing queer feminist PAR. We argue that there is an accelerating process of de-participation and exclusion that can work to erode the progressive, inclusive politics of feminist participatory methodologies.

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)0.120
metaresearch head score (Gemma)0.125
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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 score0.975
Threshold uncertainty score0.637

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.125
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0250.129
Scholarly communication0.0280.036
Open science0.0060.039
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.815
GPT teacher head0.749
Teacher spread0.067 · 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.

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

Citations25
Published2015
Admission routes1
Has abstractyes

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