The effectiveness of maternal regulatory attempts in the development of infant emotion regulation
Why this work is in the frame
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Bibliographic record
Abstract
Caregivers are instrumental in the development of infant emotion regulation; however, few studies have focused on delineating the real-time effectiveness of strategies that caregivers use to reduce infant distress. It is also unclear whether certain caregiver traits facilitate engagement in more successful regulation strategies. This study addressed these gaps by: (1) examining the differential effectiveness of maternal regulatory attempts (MRAs; behavioral strategies initiated by mothers to assist infants with regulating emotional states) in reducing 12- to 24-month-old infants' frustration during a toy removal task; and (2) assessing whether maternal mind-mindedness (mothers' attunement to their infant's mental state) predicted mothers' selection of MRAs. Multilevel modeling revealed that distraction and control were the most effective MRAs in reducing infant negative affect across 5-s intervals (N = 82 dyads; M infant age = 18 months; 45 females). Greater use of non-attuned mind-related speech predicted less engagement in effective MRAs, supporting a link between caregivers' socio-cognitive skills and provision of in-the-moment regulation support. These findings highlight the value of considering caregiver regulatory behaviors as a target for elucidating how maternal socialization of emotion regulation occurs in real-time. They also underscore mothers' important role as socializing agents in the development of this foundational developmental ability.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it