Not so fast: Individual differences in impulsiveness are only a modest predictor of cognitive reflection
Bibliographic record
Abstract
The extent to which a person engages in reflective thinking while problem-solving is often measured using the Cognitive Reflection Test (CRT; Frederick, 2005). Some past research has attributed poorer performance on the CRT to impulsiveness, which is consistent with the close conceptual relation between Type I processing and dispositional impulsiveness (and the putative relation between a tendency to engage in Type I processing and poor performance on the CRT). However, existing research has been mixed on whether such a relation exists. To address this ambiguity, we report two large sample size studies examining the relation between impulsiveness and CRT performance. Unlike previous studies, we use a number of different measures of impulsiveness, as well as measures of cognitive ability and analytic thinking style. Overall, impulsiveness is clearly related to CRT performance at the bivariate level. However, once cognitive ability and analytic thinking style are controlled, these relations become small and, in some cases, non-significant. Thus, dispositional impulsiveness, in and of itself, is not a strong predictor of CRT performance.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".