When Self‐Compassion Lacks Ferocity: Anger and Responding to False Accusations
Bibliographic record
Abstract
OBJECTIVE: Self-compassion can help people when they make mistakes, but does it affect how people respond when falsely accused of making a mistake? In this research, we tested the hypothesis that self-compassion is associated with lower levels of anger after a false accusation which, in turn, lowers the likelihood that people will attempt to challenge the accusation. METHOD: In Studies 1A (N = 422) and 1B (N = 492), participants imagined that they were playing in an important tennis match and were falsely accused by an official of making an error. In Study 2 (N = 346), participants completed an online survey that, at one point, displayed a message accusing them of plagiarizing one of their responses. RESULTS: In all studies, self-compassion assessed prior to the accusation was negatively associated with levels of anger following the accusation. Anger, in turn, was positively associated with intentions to challenge the accusation (Studies 1A and 1B) and with the likelihood that participants brought the false accusation to our attention when given an opportunity to do so (Study 2). CONCLUSION: This research shows that highly self-compassionate people are not always ferocious and may be susceptible to being taken advantage of when facing false accusations.
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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) | 0.012 | 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".