Experience Modulates Visual Search Strategies and the Effectiveness of Information Pickup to Overcome the Inversion Effect in Biological Motion Perception
Bibliographic record
Abstract
The inversion effect of biological motion suggests that presenting a point-light display in an inverted orientation would affect the observer’s ability to perceive the movement. This could be attributed to the observer’s general unfamiliarity with the dynamic characteristics of the movement after the inversion. A previous study showed that, compared to typical and non-dancers, vertical dancers were more sensitive to the artificial inversion of dance movements performed either in an upright or inverted orientation, when provided with dynamic information. This ability was attributed to vertical dancers’ unique visual and motor experience of performing movements upside down while hanging in the air. The current study aimed to replicate this finding and use eye-tracking data to identify the source of information that vertical dancers relied on to perform the judgment. Twenty dance movements were recorded either on the ground or in the air. Each pair of ground and air movements had similar forms to control the configural information. The movement was either presented as-is or inverted and the participants needed to determine whether the display was inverted. The results replicated the previous study and further showed that the higher sensitivity of vertical dancers in detecting the inverted movements was attributed to their longer and more frequent fixations on the lower torso area, where the harness was placed when performing the air movement. Although traditional dancers also attended to the lower torso area, their lack of experience with inverted movements limited their ability to interpret the observed motion for detection of the inversion.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".