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Record W4409372305 · doi:10.3390/educsci15040476

Children’s Gender Worldviews: Exploring Gender, Diversity, and Participation Through Postmodern Picture Books

2025· article· en· W4409372305 on OpenAlexaff
Carolina Gonçalves, Catarina Tomás, Aline Almeida

Bibliographic record

VenueEducation Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPostmodernismDiversity (politics)Gender studiesSociologyGender diversityPsychologyAestheticsSocial scienceEpistemologyAnthropologyArtPhilosophy

Abstract

fetched live from OpenAlex

Postmodern picture books offer valuable opportunities for children to engage with multiple perspectives and develop critical thinking skills. When used in pedagogical practices that prioritize children’s rights, agency, and voices, these books can effectively challenge dominant social norms and promote justice and equity. Within the framework of the SMOOTH project (Educational Common Spaces, Passing through Enclosures and Reversing Inequalities, Horizon 2020, EU), this qualitative study explores how children aged six to eight attending a public primary school in Lisbon, Portugal, make sense of gender through postmodern picture books. Grounded in the Educational Studies and Sociology of Childhood, the research analyses children’s understandings of gender and the meanings they construct concerning it. A six-month intervention program, consisting of read-aloud sessions, was conducted with children from diverse linguistic and socioeconomic backgrounds. Data were collected through focus groups and observation. Qualitative content analysis highlights how picture books can stimulate critical discussions on the social construction of gender, providing children with opportunities to reflect on differences, power relations, and social change. These findings indicate that embedding a care perspective further strengthens the recognition of children’s lived experiences and enriches educational practices by fostering inclusiveness and deeper understanding.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
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
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.001
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 head0.218
GPT teacher head0.398
Teacher spread0.180 · 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 teacher head, not a consensus.

Study designObservational
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

Citations2
Published2025
Admission routes1
Has abstractyes

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