The developmental course of supportive dyadic coping in couples.
Bibliographic record
Abstract
Drawing from a relational developmental systems (RDS) perspective (Lerner, Agans, DeSouza, & Gasca, 2013) and data from 1,427 continuously partnered young adult and midlife mixed-sex couples over the first 5 years of the German Panel Analysis of Intimate Relationships and Family Dynamics (pairfam), this study examined the developmental course of supportive dyadic coping, or the frequency with which one provides practical and emotional support when his or her partner encounters stress. Latent change score (LCS) modeling results revealed that supportive dyadic coping gradually declined for both male and female partners, but there was significant diversity underlying these trajectories. Higher levels of supportive dyadic coping were associated with a more gradual decline in support provided by a partner. Among young adults, a more rapid decline in male partner supportive dyadic coping predicted a slower rate of decline in support from female partners. Finally, we considered possible bidirectional relations between contextual stressors and supportive dyadic coping trajectories. Providing higher levels of support predicted a more gradual decline in self-rated health for male partners. Having more children and experiencing economic pressure predicted steeper declines in supportive dyadic coping over time for both male and female partners. (PsycINFO Database Record
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".