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Record W4415602200 · doi:10.1080/14681366.2025.2576016

Writing collaborative autoethnographic stories to understand Vietnamese children’s gendered toys

2025· article· en· W4415602200 on OpenAlexaff
Giang Nguyen Hoang Le, Vuong Tran, Thanh Minh Nguyen, Tú Anh Hà

Bibliographic record

VenuePedagogy Culture and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsVietnameseAutoethnographyEthnographyNarrativeQualitative researchAgency (philosophy)Postcolonialism (international relations)

Abstract

fetched live from OpenAlex

This paper presents our childhood memories about children’s toys as gendered in family life, school, and beyond in Vietnam. Framed by the construction of masculinity, femininity and heteronormativity, we galvanise our stories into vignettes to discuss how popular children’s toys, such as dolls and a cooking playset, could be used as a means to foster gender stereotypes in young children. In a collaborative autoethnography, we gathered our narratives in contexts of being and becoming in our early lives as children in Vietnam where we were raised to conform to adults’ gender performance expectations. Our vignettes reveal that gendered toys were instrumental for adults to shape children’s gender performances and identities in a heterosexual society. Gender-socialised toy preferences go against the notion of children having agency and being able to engage in meaning-making, which can cause diverse emotional distresses and vulnerabilities for some during their formative years and throughout their lives.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.350
Teacher spread0.332 · 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
Published2025
Admission routes1
Has abstractyes

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