Links Between Girls' Puberty and Externalizing and Internalizing Behaviors: Moving from Demonstrating Effects to Identifying Pathways
Bibliographic record
Abstract
Adolescence has fascinated developmental scholars because the transition into adolescence involves biological, psychological, and social changes (Graber & Brooks-Gunn, 1996). At the same time, adolescence has been a focus for research on psychopathology as rates of several disorders increase dramatically during this time period. Most notably, the past few decades have witnessed volumes of studies and theories on adolescent depression, conduct disorder, and subclinical psychopathology (Steinberg & Morris, 2001). Many of these studies have sought to understand the confluence of bio-psychosocial developmental factors that result in the emergence of serious behavioral and emotional problems. In this chapter, we consider several bio-psychosocial models that have been used to explain changes in internalizing and externalizing behaviors during adolescence. Examples from our own work highlight the role of pubertal development in understanding behavioral plasticity during adolescence. Discussions of plasticity in developmental processes have frequently focused on early development and gene–environment interactions in understanding development and behavior (Baltes, Lindenberger, & Staudinger, 1998). Despite a focus on the early periods of development, the notion that adaptation occurs in neural and behavioral development throughout life has been a cornerstone of life span developmental perspectives (Baltes et al., 1998; Cairns, 1998). Recent studies in neuroscience have demonstrated that new neural connections continue to be made across the life span (e.g., Bruer & Greenough, 2001) and specific changes in the prefrontal cortex and limbic regions of the brain occur during adolescence (see Spear, 2000 for a review).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".