Reasoning strategies explain individual differences in social reasoning.
Bibliographic record
Abstract
The dual-strategy model of reasoning suggests that when people reason they can either use (a) a statistical strategy which generates an estimation of conclusion likelihood using a rapid form of associative processing or (b) a counterexample strategy which identifies potential counterexamples to a conclusion using a more conscious working memory intensive process. Previous results suggest that strategy use is a strong individual difference that represents a broad distinction in the way that information is processed that goes beyond deductive reasoning. In 3 studies, we examined if this model could predict individual differences in the processing of social information by examining socially relevant cognitive biases. Study 1 found that strategy use predicted the extent of the self-serving bias. Study 2 found that strategy use predicted use of racist stereotypes even when need for closure was accounted for. Study 3 found that an essentialist prime resulted in a higher level of gender bias among statistical reasoners but that this prime had no effect on counterexample reasoners. These results indicate that the processing distinction between the 2 reasoning strategies underlies individual differences in social biases such as stereotypes, sexism, and racism. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".