The Reflective Mind: Examining Individual Differences in Susceptibility to Base Rate Neglect with fMRI
Bibliographic record
Abstract
Performance on heuristics and bias tasks has been shown to be susceptible to bias. In turn, susceptibility to bias varies as a function of individual differences in cognitive abilities (e.g., intelligence) and thinking styles (e.g., propensity for reflection). Using a classic task (i.e., lawyer-engineer problem), we conducted two experiments to examine the differential contributions of cognitive abilities versus thinking styles to performance. The results of Experiment 1 demonstrated that the Cognitive Reflection Test (CRT)-a well-established measure of reflective thinking-predicted performance on conflict problems (where base rates and intuition point in opposite directions), whereas STM predicted performance on nonconflict problems. Experiment 2 conducted in the fMRI scanner replicated this behavioral dissociation and enabled us to probe their neural correlates. As predicted, conflict problems were associated with greater activation in the ACC-a key region for conflict detection-even in cases when participants responded stereotypically. In participants with higher CRT scores, conflict problems were associated with greater activation in the posterior cingulate cortex (PCC), and activation in PCC covaried in relation to CRT scores during conflict problems. Also, CRT scores predicted activation in PCC in conflict problems (over and above nonconflict problems). Our results suggest that individual differences in reflective thinking as measured by CRT are related to brain activation in PCC-a region involved in regulating attention between external and internal foci. We discuss the implications of our findings in terms of PCC's possible involvement in switching from intuitive to analytic mode of thought.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".