MétaCan
Menu
Back to cohort
Record W2157172862 · doi:10.1080/09518390500082244

Who are the participants? Rethinking representational practices and writing with heterotopic possibility in qualitative inquiry

2005· article· en· W2157172862 on OpenAlexafffund
Marnina Gonick, Janice Hladki

Bibliographic record

VenueInternational Journal of Qualitative Studies in Education · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Southern QueenslandMcMaster UniversityPennsylvania State University
KeywordsWonderImpossibilitySociologyHeterotopia (medicine)EpistemologyRepresentation (politics)Qualitative researchSubject (documents)Identity (music)SilenceAestheticsPedagogySocial sciencePoliticsComputer science

Abstract

fetched live from OpenAlex

This paper draws on Foucault's notion of heterotopia to ask a series of questions about the important link between the crisis of representation in qualitative research and new theorizations of the ‘subject’ within poststructural feminist research. Reiterating Foucault's question, ‘what is it impossible to think and what kind of impossibility are we faced with here,’ the authors wonder how naming practices that mobilize social categories determine what is visible and thus analyzable to educational researchers. How might research writing understood as a representational practice be made to perform as a heterotopic space: a reflection on writing practices and representation itself? In engaging with these questions, the paper juxtaposes two different research projects in an attempt to set in motion readings that are—for the authors as well as for readers—self and cross‐interrogating. Each project engenders different problematizations of the ways in which identity categories are represented in research.

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)0.159
metaresearch head score (Gemma)0.137
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.841
Threshold uncertainty score0.841

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1590.137
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0180.101
Scholarly communication0.0220.036
Open science0.0040.018
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.516
GPT teacher head0.641
Teacher spread0.124 · 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 designTheoretical or conceptual
DomainMethods
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

Citations24
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Qualitative Studies in EducationSame topicPosthumanist Ethics and ActivismFrench-language works237,207