Spousal Disagreement in the Reporting of Physical Violence Against Wives in
Bibliographic record
Abstract
Using data from a probability sample of 943 married women and men in Assiut and Souhag, Egypt, we explored spousal reports of lifetime physi-cal intimate partner violence (IPV) against wives and the determinants of spousal disagreement overall and by type. More than one third of wives and about one third of husbands reported wife beating since marriage. More than one quarter of couples disagreed about its occurrence, usually be-cause wives reported wife beating when their husbands did not. Wife-yes-husband-no and wife-no-husband-yes disagreements were more common among couples who were married for more than 7 years, suggesting poor recall by either spouse of distant events, an unwillingness of husbands and wives to disclose a distant event, or variable within-couple definitions of what constitutes wife beating. Wife-yes-husband-yes and wife-yes-husband-no responses were more common among wives with little or no schooling, suggesting that these women were more likely to experience physical IPV and to have husbands who denied its occurrence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".