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Record W2945990268 · doi:10.1177/0165025419844037

Contextual variance and invariance in self-perceived gender typicality and pressure to conform to gender role expectations

2019· article· en· W2945990268 on OpenAlexafffundabout
Melisa Castellanos, Lina María Saldarriaga, Luz Stella López, William M. Bukowski

Bibliographic record

VenueInternational Journal of Behavioral Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaUniversidad del Norte
KeywordsPsychologyMeasurement invarianceConfirmatory factor analysisDevelopmental psychologySocial psychologyScale (ratio)Gender roleIdentity (music)Context (archaeology)Self-conceptCultural identityStructural equation modelingStatistics

Abstract

fetched live from OpenAlex

Evidence of cultural comparisons of gender-identity-measurement scales is scarce. The present study aims to assess the scalar invariance of two dimensions of a widely used gender identity scale (Egan and Perry’s Multidimensional Gender Identity Inventory) across two cultural contexts. Fourth, sixth, and fifth graders from Barranquilla (Colombia) and Montréal (Canada) ( n = 351) completed an abbreviated, self-report revised version of Egan and Perry’s scale. A Confirmatory Factor Analysis demonstrated that typicality and pressure to conform to traditional gender roles are distinct factors and tend to be stable over time. Furthermore, a multi-group comparison analysis showed that the measurement model did not vary significantly as a function of cultural context. Our study adds evidence to support the use of a reliable and valid measurement instrument that is invariant across cultural settings, to allow comparisons that do not depend on contextual variations in the assessment of gender identity during childhood.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
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)0.0010.000

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 head0.040
GPT teacher head0.342
Teacher spread0.302 · 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 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

Citations1
Published2019
Admission routes3
Has abstractyes

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