Karma and God: Convergent and divergent mental representations of supernatural norm enforcement
Bibliographic record
Abstract
Cultural evolutionary theories have proposed that prosocial religious traditions can facilitate societal complexity and large-scale cooperation among strangers, in part, through the culturally transmitted belief in morally concerned supernatural entities. Although a growing number of studies have documented an association between commitment to moralizing deities or forces and increased prosocial behavior, few studies have directly examined mental representations of supernaturally monitored morality, as they are reflected in world religions as conceptions of karma and God. In seven samples (total N= 3861), we use an open-ended free-list task to investigate participants’ mental representations of God and karma, among culturally diverse samples from the USA and India, including Hindu, Buddhist, Christian, and non-religious participants. Key results showed that (1) there is substantial consensus among believers that actions relevant to interpersonal cooperation (e.g., generosity, harm, fairness, and honesty) are highly relevant to both karma and God beliefs; however, (2) God is prototypically represented as a personified, social agent, who believers have a devotional relationship with, whereas karma is more commonly conceived of as a non-agentic causal process, through which moral actions generate commensurate good and bad consequences; (3) God—but not karma—is expected to reward and punish acts of religious devotion, in addition to the harm and fairness norms that characterize interpersonal prosociality; and (4) karma—much more than God—is expected to reward generosity and punish greed. These findings show how culturally-constructed religious beliefs shape expectations about the consequence of moral behavior.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".