Effects of aging on identifying emotions conveyed by point-light walkers.
Bibliographic record
Abstract
The visual system is able to recognize human motion simply from point lights attached to the major joints of an actor. Moreover, it has been shown that younger adults are able to recognize emotions from such dynamic point-light displays. Previous research has suggested that the ability to perceive emotional stimuli changes with age. For example, it has been shown that older adults are impaired in recognizing emotional expressions from static faces. In addition, it has been shown that older adults have difficulties perceiving visual motion, which might be helpful to recognize emotions from point-light displays. In the current study, 4 experiments were completed in which older and younger adults were asked to identify 3 emotions (happy, sad, and angry) displayed by 4 types of point-light walkers: upright and inverted normal walkers, which contained both local motion and global form information; upright scrambled walkers, which contained only local motion information; and upright random-position walkers, which contained only global form information. Overall, emotion discrimination accuracy was lower in older participants compared with younger participants, specifically when identifying sad and angry point-light walkers. In addition, observers in both age groups were able to recognize emotions from all types of point-light walkers, suggesting that both older and younger adults are able to recognize emotions from point-light walkers on the basis of local motion or global form.
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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 | 0.000 |
| 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".