Convergence of emotions: Correlational and experimental evidence for emotional contagion and egocentricity
Bibliographic record
Abstract
Convergence of emotions between people is ascribed in one area of research to the transfer of others’ emotions to oneself (emotional contagion), and in another as a projection of one’s own emotions onto others (emotional egocentricity). The current research sought to reconcile these two accounts by testing them simultaneously in a correlational study that measured these processes (Study 1, N = 88), and an experiment that manipulated both (Study 2, N = 329). Findings replicate the phenomenon that participants’ emotions tended to converge with the emotional expressions displayed by others. We found evidence for both emotional contagion—where others’ emotional expressions influenced that of participants—and evidence for emotional egocentricity—where participants projected their own emotions onto others. The latter occurs when others’ emotional expressions are ambiguous. These findings break new ground in the important area of emotional contagion by showing, for the first time, the cumulative effects of these processes.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".