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Record W3121298640 · doi:10.1080/03626784.2020.1864621

Drag pedagogy: The playful practice of queer imagination in early childhood

2020· article· en· W3121298640 on OpenAlexaff
Harper B. Keenan, Lil Miss Hot Mess

Bibliographic record

VenueCurriculum Inquiry · 2020
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQueerPerformative utteranceSociologyGender studiesPerformativityAestheticsEarly childhood educationPopularityPedagogyPsychologyArtSocial psychology

Abstract

fetched live from OpenAlex

In recent years, a programme for young children called Drag Queen Story Hour (DQSH) has risen to simultaneous popularity and controversy. This article, written collaboratively by an education scholar and a drag queen involved in organizing DQSH, contextualizes the programme within the landscape of gender in education as well as within the world of drag, and argues that Drag Queen Story Hour provides a generative extension of queer pedagogy into the world of early childhood education. Drawing on the work of José Esteban Muñoz, the authors discuss five interrelated elements of DQSH that offer early childhood educators a way into a sense of queer imagination: play as praxis, aesthetic transformation, strategic defiance, destigmatization of shame, and embodied kinship. Ultimately, the authors propose that “drag pedagogy” provides a performative approach to queer pedagogy that is not simply about LGBT lives, but living queerly.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0090.029
Scholarly communication0.0060.004
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.396
Teacher spread0.359 · 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

Citations93
Published2020
Admission routes1
Has abstractyes

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