Mental Rotation with Egocentric and Object-Based Transformations
Bibliographic record
Abstract
Two experiments were conducted to address methodological issues with past studies investigating the influence of egocentric and object-based transformations on performance and sex differences in mental rotation. In previous work, the egocentric and object-based mental rotation tasks confounded the stimulus type (embodied vs. non-embodied) and transformation task (egocentric vs. object-based). In both experiments presented here, the same stimuli were used regardless of the type of transformation but task instructions were modified to induce either egocentric (left-right judgment) or object-based (same-different judgment) processing. Experiment 1 used pairs of letters whereas Experiment 2 presented pairs of line-drawings of human hands. For both experiments, it was hypothesized that the mental rotation slope for response time would be steeper for object-based than for egocentric transformations. This hypothesis was verified in both experiments. Furthermore, Experiment 2 showed a reduced male advantage for egocentric compared to object-based rotations, whereas this pattern was reversed for Experiment 1. In conclusion, the present study showed that the influence of the type of transformation involved in mental rotation can be examined with the same set of stimuli simply by modifying task instructions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".