Longitudinal Relations Between Hypercompetitiveness, Jealousy, and Aggression Across Adolescence
Bibliographic record
Abstract
Numerous studies consider competition and jealousy within an evolutionary framework, yet less is known about the relation between aggression vis-à-vis hypercompetitiveness (i.e., competing to win) and jealousy. We investigated the longitudinal relations between hypercompetitiveness, jealousy, and aggression and the moderating role of gender in a sample of 615 Canadian adolescents assessed annually from Grade 7 through Grade 12 using self-reports. A developmental cascade model accounting for within-time correlations, across-time stability, and cross-lag paths was used to analyze the data. Results indicated hypercompetitiveness was positively associated with aggression across several time points (Grades 7→8, Grades 8→9, and Grades 9→10) and was associated with increased jealousy in Grades 11 and 12. Indirect aggression in Grade 12 was positively associated with higher levels of jealousy in Grade 11. Few gender differences were noted. The study provides evidence for a developmental model in which hypercompetitive and jealous youth become more aggressive over time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 teacher head, 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".