Men's regulation of anger and individual differences in empathy to children.
Bibliographic record
Abstract
The present study explored the styles and strategies men use to regulate their negative emotion and anger, as well as the relation between men's use of emotion regulation (ER) and their dispositional empathy. A sample of 120 male undergraduates imagined themselves as the father of a six-year-old child, specified as either a son or daughter. They rated the extent to which they would regulate anger toward their child, both by rating 14 general ER strategies (e.g., avoidance, positive reevaluating, giving up, hiding feelings, expressing feelings elsewhere), and by responding to two specific parenting vignettes. In addition, participants completed questionnaires assessing their ER style for negative emotion and anger (Emotion Control Questionnaire, Roger & Najarian, 1989; Anger Expression Scale, Spielberger, Reheiser, & Solomon, 1988) and their dispositional empathy (Interpersonal Reactivity Index; Davis, 1983). (Abstract shortened by UMI.)Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .K445. Source: Masters Abstracts International, Volume: 40-06, page: 1630. Adviser: Tanya S. Martini. Thesis (M.A.)--University of Windsor (Canada), 2001.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".