Caregiver unpredictability and the development of biobehavioral regulation during early childhood
Bibliographic record
Abstract
Experiences of unpredictability can create significant disruptions for children’s psychosocial development. Despite growing evidence highlighting the importance of predictable caregiving in fostering long-term healthy development, there is still limited understanding of proximal unpredictability within caregiver–child relationships. This study extended prior research on caregivers’ sensory signal unpredictability with infants, by (1) developing an observational measure of caregiver affective and behavioral unpredictability in early childhood and (2) exploring its implications for preschoolers’ development of biobehavioral self-regulation. In this longitudinal study of 98 predominantly White 4-year-old children (50% female) and their mothers, greater caregiver affective and behavioral unpredictability was associated concurrently with greater respiratory sinus arrhythmia (RSA) suppression (i.e., decrease in RSA) during the Day/Night inhibitory control task. Greater caregiver sensory signal unpredictability at 4 years predicted children’s greater RSA suppression during the Day/Night task 2 years later. Neither sensory signals nor affective or behavioral unpredictability were associated with children’s behavioral performance on the inhibitory control task. This study provides initial evidence that unpredictable caregiver signals appear to shape early, non-volitional processes that regulate arousal in novel situations, a central aspect of susceptibility to social withdrawal.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".