Emotion Differentiation During the Transition to Parenthood – Concurrent and Prospective Positive Effects
Bibliographic record
Abstract
Emotion differentiation, the extent to which same-valenced emotions are experienced in a distinct manner, has been found to be associated with various positive outcomes. However, little is known about its role in relational contexts. The present work examines couples in the transition to parenthood (TTP), a particularly emotionally demanding period, and explores the associations between emotion differentiation and both concurrent (3 months postpartum) and prospective (6 months postpartum) relationship quality. Both negative emotion differentiation (NED) and positive emotional differentiation (PED) were extracted from daily diaries completed over 21 days by both partners in 88 couples. They were then examined as predictors of relationship quality (relationship satisfaction and perceived partner responsiveness) using actor-partner interdependence models. NED was found to be concurrently associated with elevated relationship quality for one's self and for one's partner, but only when the partner's NED was low. Prospectively, partner NED was associated with greater perceived partner responsiveness and with relationship satisfaction when the actor’s NED was low. PED was found to be concurrently associated with relationship satisfaction for one’s self and one’s partner; a similar association was found for one’s own perceived partner responsiveness. Prospectively, partner PED was associated with greater relationship satisfaction. The findings suggest that NED functions as a compensatory or shared dyadic resource, and that PED, whose effects in previous studies have been mixed, may also be constructive. This suggests that individuals undergoing emotionally demanding periods (such as the TTP) may benefit from developing more nuanced emotional experiences.
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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 | 0.003 |
| 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 | 0.000 |
| 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".