The dynamic mask: Facial correlates of character portrayal in professional actors
Bibliographic record
Abstract
Actors make modifications to their face, voice, and body to match standard gestural conceptions of the fictional characters they are portraying during stage performances. However, the gestural manifestations of acting have not been quantified experimentally, least of all in group-level analyses. To quantify the facial correlates of character portrayal in professional actors for the first time, we had 24 actors portray a contrastive series of nine stock characters (e.g., king, bully, lover) that were organised according to a predictive scheme based on the two statistically independent personality dimensions of assertiveness (i.e., the tendency to satisfy personal concerns) and cooperativeness (i.e., the tendency to satisfy others' concerns). We used three-dimensional motion capture to examine changes in facial dimensions, with an emphasis on the relative expansion/contraction of four facial segments related to the brow, eyebrows, lips, and jaw, respectively. The results demonstrated that expansions in both upper- and lower-facial segments were related to increases in the levels of character cooperativeness, but not assertiveness. These findings demonstrate that actors reliably manipulate their facial features in a contrastive manner to differentiate characters based on their underlying personality traits.
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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 | 0.000 | 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 | 0.001 |
| 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 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".