Ecological Aspects of Mental Rotation Around the Vertical and Horizontal Axis
Why this work is in the frame
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Bibliographic record
Abstract
Rotation of both natural and man-made objects most commonly requires rotation around the vertical rather than the horizontal axis because it is relatively rare that we need to rotate, e.g., trees, mountains, chairs or vehicles around their horizontal axis in order to match images to their canonical orientation. Waszak, Drewing, and Mausfeld (2005) demonstrated the importance of a gravitationally defined vertical axis and the visual context within which objects occur, when performing mental rotations. We extended their findings in a between-subject design by asking 406 subjects to rotate wireframe cube figures around either the vertical axis or around the horizontal axis. Both male and female subjects performed significantly better when rotating objects around the vertical axis. Males performed better than females in both conditions, and there was no interaction between axis of rotation and sex.
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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 it