Links between friends’ behaviors and the emergence of leadership in childhood: A genetically informed study of twins
Bibliographic record
Abstract
Abstract Using a genetically informed design, this study examined whether children's leadership behavior varied as a function of their reciprocal friends’ behavioral characteristics. Specifically, we tested (a) whether friends’ use of a dual strategy (specifically, indirect aggression with prosocial behavior) was associated with children's leadership behavior and (b) whether, in line with a gene‐environment interaction (GxE), the predictive association between friends’ behaviors and children's leadership behavior varied depending on the child's genetic likelihood for leadership. The sample comprised 239 Monozygotic and same‐sex Dizygotic twin pairs (50% boys) assessed in grade 4 (mean age = 10.4 years, SD = 0.26). Reciprocal friendship and children's and their friends’ prosocial, indirectly aggressive, and physically aggressive behaviors were measured via peer nominations. Children's and friends’ leadership was measured through teacher ratings. Multilevel regression analyses revealed that children's genetic likelihood for leadership was positively associated with their leadership behavior. Moreover, the higher their genetic likelihood for leadership, the more children displayed increased leadership behavior when friends showed a combination of indirect aggression and prosocial behavior (GxE). These results underline the role of friends’ behaviors in explaining children's leadership. Socializing with bistrategic friends seems to foster leadership skills especially in children with a genetic likelihood for leadership.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".