A New Perspective on Temperamental Shyness: Differential Susceptibility to Endoenvironmental Influences
Bibliographic record
Abstract
Abstract In this review, we adapt and extend a model recently used to account for differences in risk and resiliency outcomes to explain individual differences in temperamental shyness. The differential susceptibility to environmental influences model posits that heightened biological sensitivity and reactivity in the individual can predict different outcomes for better or for worse, depending on environmental influences outside (i.e., exogenous) of the individual. In this article, we extend this existing model and argue that the environment can also be conceptualized as a unique set of dynamic conditions and influences operating within (i.e., endogenous) the individual that are orthogonal to some biological sensitivity factors. In this new model, continuous brain electrical activity at rest constitutes one endogenous environmental condition that can vary (leftward to rightward) and influence gene expression to confer different outcomes, for better (sociability) or for worse (shyness). We then discuss how this model can be tested, as well as its potential implications for theory, development, and practice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".