Multisensory determinants of orientation perception: task‐specific sex differences
Bibliographic record
Abstract
Females have been reported to be more 'visually dependent' than males. When aligning a rod in a tilted frame to vertical, females are more influenced by the frame than are males, who align the rod closer to gravity. Do females rely more on visual information at the cost of other sensory information? We compared the subjective visual vertical and the perceptual upright in 29 females and 24 males. The orientation of visual cues presented on a shrouded laptop screen and of the observer's posture were varied. When upright, females' subjective visual vertical was more influenced by visual cues and their responses were more variable than were males'. However, there were no differences between the sexes in the perceptual upright task. Individual variance in subjective visual vertical judgments and in the perceptual upright predicted the level of visual dependence across both sexes. When lying right-side down, there were no reliable differences between the sexes in either measure. We conclude that heightened 'visual dependence' in females does not generalize to all aspects of spatial processing but is probably attributable to task-specific differences in the mechanisms of sensory processing in the brains of females and males. The higher variability and lower accuracy in females for some spatial tasks is not due to their having qualitatively worse access to information concerning either the gravity axis or corporeal representation: it is only when gravity and the long body axis align that females have a performance disadvantage.
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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 | 0.001 |
| 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) | 0.004 | 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 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".