Perceived Openness to Experience Accounts for Religious Homogamy
Bibliographic record
Abstract
Two studies tested the hypothesis that religious homogamy—assortative mating on the basis of religion—can be partly explained by inferences about religious individuals’ openness to experience, rather than attitudes toward religion per se. Results of Study 1 indicated that non-religious participants perceived non-religious targets to be higher in openness and more appealing as romantic partners, with the first effect statistically accounting for the second. Study 2, which manipulated “religious” and “open” behaviors independently, showed that openness guided dating judgments for both non-religious and religious participants, albeit in opposite directions. Thus, regardless of their own religious beliefs, individuals appear to infer the same kind of behaviors from others’ religiosity, behaviors that are seen positively by religious individuals, but negatively by non-religious individuals. These inferences, in turn, partially explain all individuals’ preferences for partners of the same religious orientation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".