Reasoning strategy modulates gender differences in performance on a spatial rotation task
Bibliographic record
Abstract
The dual-strategy model of reasoning has proposed that individual differences in reasoning can be understood as due to two general ways of processing information: an analytic, counterexample strategy that examines information for explicit potential counterexamples and an intuitive, statistical strategy that uses associative access to generate a likelihood estimate of putative conclusions. Previous studies have examined this model in the context of basic conditional reasoning tasks. However, the distinctions that underlie the dual-strategy model can be seen as a basic description of more general differences in information processing. A recent study examining interactions between gender and strategy use in processing of negative emotions found that gender differences were modulated by strategy, with the general advantage of females concentrated within statistical reasoners. Two studies were performed to extend this analysis to performance on a mental rotation task for which there also exist clear gender differences. The initial study presented rotation tasks with unlimited time. Results show that males perform better on more difficult rotation tasks than females, with the difference concentrated among statistical reasoners. The second study replicated this using a restricted time (4 s) to make each judgement and showed an increase in the effect of both gender and strategy. This provides additional evidence that the dual-strategy model captures an important individual difference in the general way that information is processed.
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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) | 0.002 | 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 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".