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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 OpenAlex
Giang Nguyen Hoang Le, Vuong Tran, Thanh Minh Nguyen, Tú Anh Hà

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
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