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Record W2313025197 · doi:10.1590/1413-82712016210111

Estereotipia de Gênero nas Brincadeiras de Faz de Conta de Crianças Adotadas por Casais Homoparentais

2016· article· pt· W2313025197 on OpenAlexaff
Elder Cerqueira-Santos, Justin Bourne

Bibliographic record

VenuePsico-USF · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

Resumo O objetivo deste estudo foi investigar a estereotipia de gênero durante os episódios de brincadeiras de faz de conta entre crianças adotadas por casais homossexuais masculinos. A estereotipia de gênero nas brincadeiras infantis vem sendo constatada em diversos contextos, discutindo-se suas determinações biológica, individual e cultural. Este é um estudo observacional do qual participaram 13 crianças entre 3 a 7 anos, em 16 sessões, em uma sala de brinquedos em um Day Care no Canadá. Foram registrados 123 episódios de brincadeiras, sendo estes categorizados pela formação de grupos (número de participantes e gênero); tipo e tema das brincadeiras; e uso de objetos. Foram encontradas diferenças significativas para todos os critérios que caracterizam as brincadeiras como estereotipada para gênero, corroborando achados de estudos entre crianças educadas por casais heterossexuais. Meninos apresentaram episódios em grupos maiores e temas que exigiam mais uso do espaço, enquanto meninas brincaram em grupos menores e com mais uso de brinquedos.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.051
GPT teacher head0.327
Teacher spread0.276 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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