Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking dispositions.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, the authors argue that there are a range of effects usually studied within cognitive psychology that are legitimately thought of as aspects of critical thinking: the cognitive biases studied in the heuristics and biases literature. In a study of 793 student participants, the authors found that the ability to avoid these biases was moderately correlated with a more traditional laboratory measure of critical thinking—the ability to reason logically when logic conflicts with prior belief. The correlation between these two classes of critical thinking skills was not due to a joint connection with general cognitive ability because it remained statistically significant after the variance due to cognitive ability was partialed out. Measures of thinking dispositions (actively open-minded thinking and need for cognition) predicted unique variance in both classes of critical thinking skills after general cognitive ability had been controlled.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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