Cardiac vagal flexibility and accurate personality impressions: Examining a physiological correlate of the good judge
Bibliographic record
Abstract
OBJECTIVE: Research has long sought to identify which individuals are best at accurately perceiving others' personalities or are good judges, yet consistent predictors of this ability have been difficult to find. In the current studies, we revisit this question by examining a novel physiological correlate of social sensitivity, cardiac vagal flexibility, which reflects dynamic modulation of cardiac vagal control. METHOD: We examined whether greater cardiac vagal flexibility was associated with forming more accurate personality impressions, defined as viewing targets more in line with their distinctive self-reported profile of traits, in two studies, including a thin-slice video perceptions study (N = 109) and a dyadic interaction study (N = 175). RESULTS: Across studies, we found that individuals higher in vagal flexibility formed significantly more accurate first impressions of others' more observable personality traits (e.g., extraversion, creativity, warmth). These associations held while including a range of relevant covariates, including cardiac vagal tone, sympathetic activation, and gender. CONCLUSION: In sum, social sensitivity as indexed by cardiac vagal flexibility is linked to forming more accurate impressions of others' observable traits, shedding light on a characteristic that may help to identify the elusive good judge and providing insight into its neurobiological underpinnings.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".