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Record W2099984802 · doi:10.1037/0012-1649.43.1.13

Gender differences in physical aggression: A prospective population-based survey of children before and after 2 years of age.

2007· article· en· W2099984802 on OpenAlexafffund
Raymond H. Baillargeon, Mark Zoccolillo, Kate Keenan, Sylvana M. Côté, Daniel Pérusse, Hong‐Xing Wu, Michel Boivin, Richard E. Tremblay

Bibliographic record

VenueDevelopmental Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversité LavalHealth CanadaMcGill UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchUniversité de Montréal
KeywordsAggressionPsychologySocializationDevelopmental psychologyPopulationInjury preventionPoison controlDemographyMedicine

Abstract

fetched live from OpenAlex

There has been much controversy over the past decades on the origins of gender differences in children's aggressive behavior. A widely held view is that gender differences emerge sometime after 2 years of age and increase in magnitude thereafter because of gender-differentiated socialization practices. The objective of this study was to test for (a) gender differences in the prevalence of physical aggression in the general population of 17-month-old children and (b) change in the magnitude of these differences between 17 and 29 months of age. Contrary to the differential socialization hypothesis, the results showed substantial gender differences in the prevalence of physical aggression at 17 months of age, with 5% of boys but only 1% of girls manifesting physically aggressive behaviors on a frequent basis. The results suggest that there is no change in the magnitude of these differences between 17 and 29 months of age.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.322
Teacher spread0.298 · 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

Citations248
Published2007
Admission routes2
Has abstractyes

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