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Record W4389816327 · doi:10.1111/chso.12826

Doing and undoing gendered racism with racialized girls: A school‐based youth participatory action research study

2023· article· en· W4389816327 on OpenAlexaffabout
Leila Angod

Bibliographic record

VenueChildren & Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsCarleton University
Fundersnot available
KeywordsParticipatory action researchSociologyAction researchTransformative learningGender studiesRacismUndoingDialogicPedagogyPsychologyAnthropology

Abstract

fetched live from OpenAlex

Abstract This article explores the ethics and transformative potential of youth participatory action research (yPAR) using data from a 2‐year school‐based yPAR study at an elite, independent school in Toronto, Canada. I use discourse analysis to show how school‐based yPAR with racialized girls intensified their experiences of gendered racism, shaping the research in a circular fashion. I demonstrate how youth researchers' strategies for counteracting this intensification contradicted the project's critical race feminist investments. This study concludes that yPAR facilitators must address the potential/actual harm of youth researchers' involvement in yPAR as part of the research process.

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)0.025
metaresearch head score (Gemma)0.011
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 score0.058
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0280.017
Scholarly communication0.0080.003
Open science0.0020.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.751
GPT teacher head0.647
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

Citations1
Published2023
Admission routes2
Has abstractyes

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