Raging Hormones in Puberty: Do They In‡uence Adolescent Risky Behavior?
Bibliographic record
Abstract
The rapid and dramatic changes in hormone levels during adolescence have been linked to the onset of a number of problematic behaviors. Using a unique data set that contains information on testosterone and cortisol levels, we examine whether these variables directly aect a variety of outcomes and indirectly aect the magnitude and interpretation of several key family background variables. Further, using information on access to two randomly assigned interventions designed to promote child development we identify the causal eect of alternative child rearing practices. We …nd strong evidence that child rearing practices are endogenous and that active super- vision is substantially more eective than simply imposing rules. Testosterone levels and their growth rates are signi…cantly associated to a variety of risky and criminal activities. Cortisol levels are related to gang activity, property crime and illicit drug use. While the inclusion of hormones is found to have minor impacts on parental education and income, they substantially aect the magnitude and signi…cance of adolescent height. Finally, although we …nd adolescent hormone levels are not correlated with birth outcomes or early behavior, we suggest they may proxy for the dynamic relationship between genes and an individual's environment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".