Maternal Into‐The‐Face Behavior, Shared Attention, and Infant Distress During Face‐to‐Face Play at 12 Months: Bi‐directional Contingencies
Bibliographic record
Abstract
We describe a new maternal intrusion behavior, moving a toy or hand “into‐the‐face” of the infant, and we investigate its bi‐directional associations with infant‐initiated shared attention, infant distress, and infant gaze, during mother–infant face‐to‐face play at 12 months. The play was videotaped split‐screen, with infants seated in a high chair. Videotapes were coded on a 1‐sec time base for mother and infant gaze (at partner, toy, both, or gaze away); infant distress; and maternal intrusion behavior, “into‐the‐face.” We defined “infant‐initiated shared attention” as mother and infant looking in the same second at a toy that the infant‐initiated interest in. We documented that maternal into‐the‐face behavior decreased the likelihood of infant‐initiated shared attention, increased the likelihood of infant distress, and decreased the likelihood of infant gazing away. Reciprocally, infant distress and gazing away increased the likelihood of mother into‐the‐face. In moments when the dyad was engaged in infant‐initiated shared attention, mother into‐the‐face was less likely. This work documents bi‐directional contingencies in the regulation of maternal intrusion and infant behavior during face‐to‐face play at 12 months. We suggest that mother into‐the‐face behavior disturbs an aspect of the infant's experience of recognition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".