Couple Religiosity, Male Headship, Intimate Partner Violence, and Infidelity
Bibliographic record
Abstract
Background The research literature finds a positive relationship between couple religiosity and relationship quality, but because public discourse highlights religious victims of domestic violence, we questioned whether couple religiosity prevents negative relationship outcomes as well as it promotes positive ones. Purpose This article compares rates of intimate partner violence (IPV) and infidelity among couples with different levels of religious commitment. We further interrogated whether the belief that the man is the head of the household increased couples’ risk of IPV or infidelity. Methods We used Global Family and Gender Survey data from eleven countries. This was an online survey of adults ages 18 to 50 that used a representative panel for the United States, but used opt-in panels in Australia, France, Ireland, United Kingdom, Canada, Argentina, Chile, Colombia, Mexico, and Peru. We limited our analytic sample to the 9920 men and women in heterosexual relationships (6791 married and 3128 cohabiting). We also analyzed the United States probability sample separately from our pooled sample. Results Couples with nominal or unequal religiosity ( less/mixed religious couples) had higher rates of infidelity than either highly religious couples or couples in which neither partner exhibited much religiosity ( shared secular couples). Infidelity was generally similar between highly religious couples and shared secular couples, but in the US women in highly religious couples did cheat less. We found no differences in IPV—measured by both women's reports of victimization and men's reports of perpetration—according to couple religiosity. Further, the belief that the man is the head of the household did not influence couples’ risk of either IPV or infidelity across the entire sample. In Latin America, however, patriarchal men in shared secular couples perpetrated IPV significantly more often than their egalitarian or more religious counterparts. Conclusions and Implications Our Latin American evidence hints that patriarchy may be a more dangerous ideology for secular couples than for religious couples. Our more general conclusion is that even though negative relationship outcomes are not more common among religious couples, the resources religious traditions have at their disposal to discourage violence within intimate partnerships seem tragically underutilized.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".