The prototypical pride expression: Development of a nonverbal behavior coding system.
Bibliographic record
Abstract
This research provides a systematic analysis of the nonverbal expression of pride. Study 1 manipulated behavioral movements relevant to pride (e.g., expanded posture and head tilt) to identify the most prototypical pride expression and determine the specific components that are necessary and sufficient for reliable recognition. Studies 2 and 3 tested whether the 2 conceptually and empirically distinct facets of pride ("authentic" and "hubristic"; J. L. Tracy & R. W. Robins, 2007a) are associated with distinct nonverbal expressions. Results showed that neither the prototypical pride expression nor several recognizable variants were differentially associated with either facet, suggesting that for the most part, authentic and hubristic pride share the same signal. Together these studies indicate that pride can be reliably assessed from nonverbal behaviors. In the Appendix, the authors provide guidelines for a pride behavioral coding scheme, akin to the Emotion Facial Action Coding System (EMFACS; P. Ekman & E. Rosenberg, 1997) for assessing "basic" emotions from observable nonverbal behaviors.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".