Role of parenting on self-regulation from a cross-cultural perspective: Major empirical findings from the first quarter of the 21st century
Bibliographic record
Abstract
This paper focuses on the extant evidence about the ways children around the globe master self-regulation (SR). Our goal was to summarize emerging evidence on cross-cultural comparison of SR in young children, and evaluate culturally common as well as distinct caregiver-child interaction patterns in relation to SR. Studies retrieved from major databases spanning from 2000 to 2025 were selected if they entailed samples of caregiver-infant/toddler dyads and compared at least two cultural groups. Ethnographic field studies and in-depth interview studies on emotion-related socialization for SR were also included. Findings were presented in three sections. First, the definition of SR and its milestones in early childhood are presented. Second, taking the cultural pathways as a conceptual framework, key findings from cross-cultural research with samples of infants and toddlers are synthesized that included studies on Face-to-Face Still-Face paradigm, moment-to-moment co-regulation, compliance, emotion regulation, and temperamental effortful control. Evidence supports both cultural universals and distinct socialization processes for the development of SR. In the third section, key conclusions are discussed in light of the cultural pathways hypothesis. The final section entails recommendations to advance future research, both theoretically and methodologically.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".