Being Good Without God: Moral Similarity Between Theists and Atheists Leads to Collective Angst and Prejudice Against Atheists
Bibliographic record
Abstract
Research suggests that the prejudices theists hold against atheists stems from the perception that atheists lack a source of moral guidance normally provided by religious belief.Due to this perceived lack of morality, theists often judge atheists as being distrustful social deviants or rogues (see Gervais & Norenzayan, 2012).As theists perceive atheists as morally lacking, and therefore untrustworthy, perceiving atheists as morally similar to theists should bolster trust in atheists.Prejudice against atheists should be reduced insofar as theists perceive atheists as holding common moral values (see Edgell, Gerteis, & Hartmann, 2006).However, seeing as increased moral similarity between atheists and theists should be threatening to theists' religious social identity, theists may express prejudice against atheists when they perceive atheists as morally similar.Indeed, in Study 1 (N = 62), I found that prejudice against atheists occurs when religious people perceive atheists as sharing their religious group's morality and that this relationship was a function of fear for the future of their social group (i.e., collective angst).Of note, this relationship was only significant for participants who had a strong Christian identity.In Study 2 (N = 145), I experimentally tested the e↵ects of moral similarity (versus moral di↵erence) on collective angst and in turn prejudice against atheists for participants with varying degrees of Christian identity.The model in Study 2 did not support the correlational findings of Study 1.The implications of these models will be discussed. Keywords: atheists,
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 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".