What really helps? Divergent implications of talking to someone with an empathic mindset versus similar experience for shame and self‐evaluation in the wake of an embarrassing event
Bibliographic record
Abstract
What kinds of social interactions help individuals recover from an embarrassing experience? The present experiment examined the possibility that whereas individuals do not benefit from interacting with someone who is merely trying to understand and empathize, they do benefit from interacting with someone who has undergone the same experience and thus accurately understands their feelings. The 'target' member of 142 dyads performed an embarrassing task in front of the 'perceiver', after which they had a face-to-face discussion. Unbeknownst to targets, some perceivers did the task themselves beforehand, and some perceivers adopted an empathic mindset during the exchange. Perceivers' previous experience predicted improvements in targets' self-evaluations that were mediated by more accurate perceptions of targets' feelings. In contrast, perceivers' empathic mindset had no benefits for targets, alone or in concert with prior experience. The only apparent benefits of perceivers' empathic mindset were that perceivers felt more empathy and liking for targets (both undetected by targets), and felt viewed more favourably by targets (not corroborated by targets). These results suggest greater efficacy of perceiver experience over empathic concern in facilitating targets' recovery from embarrassing events. Perceivers' dispositional empathy, involving a different type of experience accumulated over time, also predicted benefits to targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".