Development of shyness across adolescence: Reactivity, regulation, or both?
Bibliographic record
Abstract
The reactivity-regulation model suggests that the origins and maintenance of shyness results from relatively high levels of reactivity in combination with relatively low levels of regulation. Although this model has received some empirical support, there are still issues regarding directionality of the relations among variables and a dearth of studies examining the joint influence of reactivity and regulation on the prospective development of shyness. Using a longitudinal design, we first examined whether the relations among reactivity, regulation, and shyness were unidirectional or bidirectional in a sample of 1284 children (49.8% female, 84.1% White; mean parental education fell between associate degree/diploma and undergraduate degree) assessed annually across three waves from late childhood and early adolescence (Mage = 10.72 years) to adolescence (Mage = 12.42 years) and then examined whether reactivity and regulation interacted to influence the development of shyness over time. At Wave 1, shyness was related to higher levels of reactivity and lower levels of regulation at Wave 2, but neither reactivity nor regulation at Wave 1 predicted shyness at Wave 2. At Wave 2, shyness predicted greater reactivity at Wave 3, but shyness at Wave 3 was only predicted by lower levels of regulation at Wave 2. Contrary to the reactivity-regulation model of shyness, we found that relatively high levels of reactivity and low levels of regulation predicted a steep decrease in shyness over 3 years. These results are discussed in the context of the socioemotional difficulties experienced by shy individuals and demonstrate the importance of empirically evaluating long-standing models of personality development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".