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Record W4407825453 · doi:10.26443/mje/rsem.v58i3.10092

Postfeminism at play: Pretend play with Disney princess transmedia in the early childhood education classroom

2024· article· en· W4407825453 on OpenAlexaffvenueabout
Tifanie Valade

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEarly childhood educationPsychologyEarly childhoodSociologyPedagogyVisual artsDevelopmental psychologyArtAdvertising

Abstract

fetched live from OpenAlex

This article examines how young children take up gender and sexuality discourses embedded in Disney Princess transmedia narratives and merchandise. A feminist ethnographic study conducted in two Canadian early childhood education and care (ECEC) classrooms found that young children often take up stereotypically gendered, heteronormative roles from princess transmedia during pretend play. The author contends that princess play includes problematic postfeminist themes, yet also offers agentic, pleasurable roles for children to embody. Disney’s hyperfeminine princess aesthetic is sometimes utilized by girls to subvert inequitable gender hierarchies and claim powerful positions within play scenarios. However, femmephobia can result in reinforcement of hegemonic gender discourses via gender policing. Implications for gender equity in ECEC environments are discussed.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.161
GPT teacher head0.398
Teacher spread0.237 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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