A pedestrian courtship: Attractiveness and symmetry of humans walking
Bibliographic record
Abstract
People are more than faces, and much of our perception of others derives from visual appraisal of bodies and their movement — rich sources of information as to gender, identity, etc. We find that, even ignoring overt courtship displays (eg, dancing), the mere act of walking, a ubiquitous human activity, provides observers a compelling percept of attractiveness. Previously, we demonstrated the influence of sexual dimorphism and prototypicality on attractiveness of human gait; here we extend this to examine the role of symmetry. To do so, we obtain attractiveness ratings for motion-captured women, displayed as point-light walkers, and for their perfectly symmetric counterparts. Our results show that making symmetric an individual's body and movement can indeed increase attractiveness, although this benefit might not be seen for less attractive individuals. Moreover, a key feature of our approach (Troje, 2002) is the ability to independently manipulate the symmetry of either the body or its movement and thus investigate the contribution of each to attractiveness. Whereas previously examined anatomical asymmetries may be quite small and difficult to measure and to perceive visually, we propose that asymmetries in movement may be more readily observed and salient. Our results thus far indicate that, at least for more attractive individuals, symmetry of movement has a greater bearing on attractiveness than does anatomic symmetry. In conclusion, we suggest that explicitly and independently manipulating anatomic and kinematic symmetry (and sexual dimorphism, prototypicality, etc) of motion-captured individuals provides an important complement to existing correlational and video-based methods in the study of person perception.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".