Logical Intuition Is Not Really About Logic
Bibliographic record
Abstract
Recent research suggest that reasoners are able to draw simple logical or probabilistic inferences relatively intuitively and automatically, a capacity which has been termed “logical intuition” (see, for example, De Neys & Pennycook, 2019). A key finding in support of this interpretation is that conclusion validity consistently interferes with judgments of conclusion believability, suggesting that information about logical validity is available quickly enough to interfere with belief judgments. In this paper we examined whether logical intuitions arise because reasoners are sensitive to the logical features of problem or another structural feature that just happens to aligns with logical validity. In three experiments (N = 113, 137, and 122), we presented participants with logical (determinate) and pseudo-logical (indeterminate) arguments and asked them to judge the validity or believability of the conclusion. Logical arguments had determinately valid or invalid conclusions, whereas pseudo-logical arguments were all logically indeterminate, but some were pseudo-valid (possible ‘strong’ arguments) and others pseudo-invalid (possible ‘weak’ arguments). Experiments 1 and 2 used simple Modus Ponens and Affirming the Consequent structures; Experiment 3 used more complex Denying the Antecedent and Modus Tollens structures. In all three experiments, we found that pseudo-validity interfered with belief judgments to the same extent as real validity. Altogether, these findings suggest that whilst people are able to draw inferences intuitively, and these inferences impact on belief judgments, they are not ‘logical intuitions.’ Rather, the intuitive inferences are driven by the processing of more superficial structural features that happen to align with logical validity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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; both teacher heads agree on what is shown here.
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".