Multiple emotions: A person-centered approach to the relationship between intergroup emotion and action orientation.
Why this work is in the frame
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Bibliographic record
Abstract
Although a great deal of research has investigated the relationship between emotions and action orientations, most studies to date have used variable-centered techniques to identify the best emotion predictor(s) of a particular action. Given that people frequently report multiple or blended emotions, a profitable area of research may be to adopt person-centered approaches to examine the action orientations elicited by a particular combination of emotions or "emotion profile." In two studies, across instances of intergroup inequality in Australia and Canada, we examined participants' experiences of six intergroup emotions: sympathy, anger directed at three targets, shame, and pride. In both studies, five groups of participants with similar emotion profiles were identified by cluster analysis and their action orientations were compared; clusters indicated that the majority of participants experienced multiple emotions. Each action orientation was also regressed on the six emotions. There were a number of differences in the results obtained from the person-centered and variable-centered approaches. This was most apparent for sympathy: the group of participants experiencing only sympathy showed little inclination to perform prosocial actions, yet sympathy was a significant predictor of numerous action orientations in regression analyses. These results imply that sympathy may only prompt a desire for action when experienced in combination with other emotions. We suggest that the use of person-centered and variable-centered approaches as complementary analytic strategies may enrich research into not only the affective predictors of action, but emotion research in general.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it