Automatic imitation is reduced in narcissists.
Bibliographic record
Abstract
Narcissism is a personality trait that has been extensively studied in normal populations. Individuals high on subclinical narcissism tend to display an excessive self-focus and reduced concern for others. Does their disregard of others have roots in low-level processes of social perception? We investigated whether narcissism is related to the automatic imitation of observed actions. In the automatic imitation task, participants make cued actions in the presence of action videos displaying congruent or incongruent actions. The difference in response times and accuracy between congruent and incongruent trials (i.e., the interference effect) is a behavioral index of motor resonance in the brain-a process whereby observed actions activate matching motor representations in the observer. We found narcissism to be negatively related to interference in the automatic imitation task, such that high narcissism is associated with reduced imitation. Thus, levels of narcissism predict differences in the tendency to automatically resonate with others, and the pattern of data we observe suggests that a key difference is that high narcissists possess an improved ability to suppress automatic imitation when such imitation would be detrimental to task performance. To the extent that motor resonance is a product of a human mirror system, our data constitute evidence for a link between narcissistic tendencies and mirror system functioning.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".