Gender Differences in Young Children's Temperament Traits: Comparisons Across Observational and Parent‐Report Methods
Bibliographic record
Abstract
Evidence supporting the continuity between child temperament and adult personality traits is accumulating. One important indicator of continuity is the presence of reliable gender differences in traits across the lifespan. A substantial literature demonstrates gender differences on certain adult personality traits and recent meta-analytic work on child samples suggests similar gender differences for some broad and narrow domains of temperament. However, most existing studies of children rely only on parent-report measures. The present study investigated gender differences in temperament traits assessed by laboratory observation, maternal-report, and paternal-report measures. Across three independent samples, behavioral observations, maternal-report, and paternal-report measures of temperament were collected on 463 boys and 402 girls. Across all three methods, girls demonstrated higher positive affect and fear and lower activity level than boys. For laboratory measures, girls demonstrated higher levels of sociability and lower levels of overall negative emotionality (NE), sadness, anger and impulsivity than boys. However, girls demonstrated higher levels of overall NE and sadness than boys when measured by maternal reports. Finally, girls demonstrated lower levels of sociability based on paternal reports. Results are discussed in relation to past meta-analytic work and developmental implications of the findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".