Real‐Time Contingencies of Emotion Socialization During Parent–Adolescent Conflicts
Bibliographic record
Abstract
ABSTRACT Parent–adolescent emotion socialization (ES) is theoretically a moment‐to‐moment (i.e., real‐time), bidirectional process in which emotional moments are opportunities for directing youth's longer‐term socioemotional development. However, due to reliance on static and self‐report measurement, we know little about this process during this age period. The objective of this study was to examine this process directly by assessing the real‐time dynamic interplay of ES behaviors and affect during typical parent–adolescent interactions. These dynamics were measured within a 4‐min conflict discussion between mothers and adolescents (12–13‐year‐olds, N = 164) using the Parent ES in Adolescence coding system to capture the full range of mothers’ supportive and unsupportive ES. Real‐time adolescents’ and mothers’ expressed affective valence was also measured. Dynamic structural equation modeling (SEM) was used to analyze how affect predicted ES and how ES predicted affect across 5‐s increments, with dyadic relationship quality (DRQ) and adolescent gender as between‐dyad predictors. Findings revealed that adolescent affect (A‐Affect) positively predicted Supportive‐ES but did not predict Unsupportive‐ES. Supportive‐ES was followed by a decrease in Adolescents’ and Mothers’ Affect, whereas Unsupportive‐ES had the opposite effect. Gender did not predict differences in real‐time effects, but higher DRQ was related to more flexible dyadic affect dynamics and greater increases in A‐Affect following Unsupportive‐ES. Findings are discussed as both the product of ES processes that had transpired prior to our time of measurement, as well as a potential predictor of future socioemotional development.
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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 | 0.006 |
| 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 | 0.001 | 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".