Comparing integral and incidental emotions: Testing insights from emotions as social information theory and attribution theory.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Studies have indicated that observers can infer information about others' behavioral intentions from others' emotions and use this information in making their own decisions. Integrating emotions as social information (EASI) theory and attribution theory, we argue that the interpersonal effects of emotions are not only influenced by the type of discrete emotion (e.g., anger vs. happiness) but also by the target of the emotion (i.e., how the emotion relates to the situation). We compare the interpersonal effects of emotions that are integral (i.e., related to the situation) versus incidental (i.e., lacking a clear target in the situation) in a negotiation context. Results from 4 studies support our general argument that the target of an opponent's emotion influences the degree to which observers attribute the emotion to their own behavior. These attributions influence observers' inferences regarding the perceived threat of an impasse or cooperativeness of an opponent, which can motivate observers to strategically adjust their behavior. Specifically, emotion target influenced concessions for both anger and happiness (Study 1, N = 254), with perceived threat and cooperativeness mediating the effects of anger and happiness, respectively (Study 2, N = 280). Study 3 (N = 314) demonstrated the mediating role of attributions and moderating role of need for closure. Study 4 (N = 193) outlined how observers' need for cognitive closure influences how they attribute incidental anger. We discuss theoretical implications related to the social influence of emotions as well as practical implications related to the impact of personality on negotiators' biases and behaviors. (PsycINFO Database Record
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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 | 0.001 |
| 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