Caregiving adversity during infancy and preschool cognitive function: adaptations to context?
Bibliographic record
Abstract
From a conditional adaptation vantage point, early life caregiving adversity likely enhances aspects of cognition needed to manage interpersonal threats. Yet, research examining early life care and offspring cognition predominantly relies upon experiments including affectively neutral stimuli, with findings generally interpreted as "early-life caregiving adversity is, de facto, 'bad' for cognitive performance." Here, in a Southeast Asian sample, we examined observed maternal sensitivity in infancy and cognitive performance 3 years later as preschoolers took part in three tasks, each involving both a socioemotional (SE) and non-socioemotional (NSE) version: relational memory (n = 236), cognitive flexibility (n = 203), and inhibitory control (n = 255). Results indicate the relation between early life caregiving adversity and memory performance significantly differs (Wald test = 7.67, (1), P = 0.006) depending on the SE versus NSE context, with maternal sensitivity in infancy highly predictive of worse memory for SE stimuli, and amongst girls, also predictive of better memory when NSE stimuli are used. Results concerning inhibitory control, as well as cognitive flexibility in girls, also tentatively suggest the importance of considering the SE nature of stimuli when assessing relations between the caregiving environment and cognitive performance. As not all approaches to missing data yielded similar results, implications for statistical approaches are elaborated. We conclude by considering how an adaptation-to-context framework approach may aid in designing pedagogical strategies and well-being interventions that harness pre-existing cognitive strengths.
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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 | 0.002 |
| 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 | 0.001 |
| 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".