How is analytical thinking related to religious belief? A test of three theoretical models
Bibliographic record
Abstract
A growing literature has documented a negative association between analytical thinking style and belief in God. However, the replicability, magnitude, and theoretical importance of this correlation has recently been debated. Moreover, the existing literature has not examined distinct psychological accounts of this relationship. In Study 1, we (1) tested the replicability of the correlation and assessed its magnitude in a large sample (N = 5284; comprising of undergraduate students at a Canadian university, and broader samples of Canadians, Americans and Indians); and (2) tested three distinct theoretical accounts of how cognitive style might come to be related to a diverse set of religious beliefs including belief in God, in karma, and in witchcraft. The first, the dual process model, posits that analytical thinking is inversely related to belief in God and in other supernatural entities. The second, the expressive rationality model, posits that analytical thinking is specifically recruited in supporting already-held beliefs in an identity-protective manner. And the third, the counter-normativity rationality model, posits that analytical thinking is recruited to question beliefs supported by prevailing cultural norms. We tested specific predictions derived from these models regarding the association between analytic thinking and religious beliefs in a Bayesian framework. In Study 2, we tested the replicability of our results in a re-analysis of previously-published data. We conclude that whereas the counter-normativity rationality model was contradicted by the data, both the dual process and expressive rationality models received limited empirical support.
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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 | 0.051 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".