Low and Middle Income Mothers’ Regulation of Negative Emotion: Effects of Children's Temperament and Situational Emotional Responses
Bibliographic record
Abstract
Abstract The present study investigated the effects of situational (child situational emotions) and dispositional (child temperament) child variables on mothers’ regulation of their own hostile (anger) and nonhostile (sadness and anxiety) emotions. Participants included 94 low and middle income mothers and their children (41 girls; 53 boys) aged 3 to 6 years. Children's situational emotions (anger, sadness, or fear) and parent emotion type (hostile or nonhostile) were important predictors of mothers’ regulation, but their effects were influenced by SES: Middle income mothers were more likely to control hostile than nonhostile emotions in response to child anger and sadness, and more likely than low income mothers to control hostile emotions in response to child sadness and fear. Low income mothers were more likely than middle income mothers to control nonhostile emotions in response to child anger. However, results also suggest that differences in emotion regulation between low and middle income mothers may stem from the link between SES and authoritarian parenting beliefs. Maternal regulation of negative emotion was not predicted by child temperament.
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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 | 0.000 | 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".