The Role of Maternal Affect Mirroring on Social Expectancies in Three-Month-Old Infants
Bibliographic record
Abstract
The role of maternal affect mirroring on the development of prosocial behaviors and social expectancies was assessed in forty-one 2- to 3-month-old infants. Prosocial behavior was characterized as infants' positive behavior and increased attention toward their mothers. Social expectancies were defined as infants' expectancy for affective sharing. Mothers and infants were observed twice, approximately 1 week apart. During Visit 1, mothers and infants were videotaped while interacting over television monitors for 3 min. During Visit 2, infants engaged in a live, 3-min interaction with their mothers over television monitors (live condition) and they also viewed a replay of their mothers' interaction from the preceding week (replay condition). The order of conditions was counterbalanced. Maternal affect mirroring was measured according to the level of attention maintenance, warm sensitivity, and social responsiveness displayed. A natural split was observed with 58% of the mothers ranking high and 42% ranking low on these affect mirroring measures (HAM and LAM, respectively). Infants in the HAM group ranked high on prosocial behaviors and social expectancy--they discriminated between live and replay, conditions with smiles, vocalizations, and gazes. Infants in the LAM group ranked low on these variables--they gazed longer during the live condition than during the replay condition, but only when the live condition was presented first; however, they did not smile or vocalize more. These findings indicate that there is a relation between affect mirroring and social expectancies in infants.
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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 | 0.000 | 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) | 0.001 | 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".