Emotion regulation strategies and goals as predictors of older mothers’ and adult daughters’ helping-related subjective well-being.
Bibliographic record
Abstract
We examined emotion regulation (ER) in intergenerational helping relationships involving 77 older mother-adult daughter dyads. Participants' ER strategies (passive, proactive) and ER goals (self-oriented, other oriented) were considered as predictors of their own and their partners' satisfaction with, and their positive and negative affective reactions to, the helping relationship. For mothers and daughters, greater use of passive ER strategies predicted greater negative affect, lower satisfaction, and less positive affect for themselves, as well as partner reports of lower satisfaction and (for daughters only) greater negative affect. Mothers' and daughters' use of proactive strategies predicted lower negative affect for themselves, and daughters' use of proactive ER strategies predicted lower negative affect for their mothers. Mothers' and daughters' endorsement of other-oriented ER goals predicted greater satisfaction and positive affect for themselves. Results are considered in the context of the larger literature concerning intergenerational helping relationships.
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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 | 0.004 |
| 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".