Female employment and Spousal abuse: A parallel cross-country analysis of developing countries
Bibliographic record
Abstract
This study explores how domestic violence and female employment interact and impact female economic empowerment in developing economies. Using micro data data from 35 countries (Central Africa, West Africa, East Africa, South Asia, Central Asia, and Southeast Asia, Middle East & North Africa, and Latin America), the effect of women’s employment on reported domestic violence is estimated. An instrumental Variables technique is used to correct for the potential endogeneity of women’s employment, which might bias the relationship between employment and domestic violence. The study also attempts to do an in-depth analyses on the linkage between types of domestic violence and break down results by region. Without taking endogeneity into account, the estimation suggests that woman’s employment increases violence by her spouse. After controlling for endogeneity, these results turn out to be the opposite, which suggests that women’s employment status has a negative influence on domestic violence. Breaking down the estimation by region shows that women’s employment decreases domestic violence in all regions except Latin America and East Africa. Differentiating by employment type shows that women working in agricultural occupations experience more marital abuse.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".