Cognitive Pathways to Belief in Karma and Belief in God
Bibliographic record
Abstract
Supernatural beliefs are ubiquitous around the world, and mounting evidence indicates that these beliefs partly rely on intuitive, cross-culturally recurrent cognitive processes. Specifically, past research has focused on humans' intuitive tendency to perceive minds as part of the cognitive foundations of belief in a personified God-an agentic, morally concerned supernatural entity. However, much less is known about belief in karma-another culturally widespread but ostensibly non-agentic supernatural entity reflecting ethical causation across reincarnations. In two studies and four high-powered samples, including mostly Christian Canadians and mostly Hindu Indians (Study 1, N = 2,006) and mostly Christian Americans and Singaporean Buddhists (Study 2, N = 1,752), we provide the first systematic empirical investigation of the cognitive intuitions underlying various forms of belief in karma. We used path analyses to (a) replicate tests of the previously documented cognitive predictors of belief in God, (b) test whether this same network of variables predicts belief in karma, and (c) examine the relative contributions of cognitive and cultural variables to both sets of beliefs. We found that cognitive tendencies toward intuitive thinking, mentalizing, dualism, and teleological thinking predicted a variety of beliefs about karma-including morally laden, non-agentic, and agentic conceptualizations-above and beyond the variability explained by cultural learning about karma across cultures. These results provide further evidence for an independent role for both culture and cognition in supporting diverse types of supernatural beliefs in distinct cultural contexts.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".