On the role of analytic thinking in religious belief change: Evidence from over 50,000 participants in 16 countries
Bibliographic record
Abstract
Religious beliefs are among the most ubiquitous ideological beliefs in the world and often critical to people’s worldview. Nonetheless, there is a great deal of variability in the strength and persistence of such beliefs, both across and within cultures. Here, we are interested in what underlying cognitive processes are associated with the phenomena of religious belief change. Although previous research has linked the tendency to engage in analytic thinking with religious dis-belief, this work has missed the potentially larger relationship between analytic thinking and belief change more broadly – that is change in any/either direction. Across two large datasets, including 16 countries and 50,827 individuals, we found that roughly 25% of individuals indicated having substantively changing their beliefs at least once. Further, the relationship between analytic thinking and belief change appears independent from the association between analytic thinking and reported level of belief. Therefore, although analytic thinking is generally associated with a decrease in religious belief, we find some evidence that it may also support an increase in belief among those indicating past change. In total, this work provides evidence for a robust link between analytic thinking and religious belief change over time.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".