Bibliographic record
Abstract
CONTEXT: Previous studies have established women's autonomy as an important determinant of several demographic outcomes in Sub-Saharan Africa, yet very few have considered intimate partner violence as one of these outcomes. METHODS: Data collected in 2017 from 2,289 women residing in 40 communities in Ghana were used to examine associations between three types of autonomy-economic decision making, family planning decision making and sexual autonomy-and women's experiences with physical, sexual, emotional and economic violence. Multilevel logistic regression was used to identify associations. RESULTS: All three types of autonomy were associated with having experienced intimate partner violence, although in different ways, at the individual level or community level. At the individual level, after adjustment for theoretically relevant variables, family planning decision-making autonomy was negatively associated with all four types of violence (odds ratios, 0.7-0.8), while economic decision-making autonomy was positively associated with emotional and economic violence (1.2 for each). At the community level, living in a community where women had higher levels of sexual autonomy was associated with reduced odds of having experienced physical and economic violence (0.5 and 0.4, respectively). CONCLUSIONS: The findings underscore the relevance of women's empowerment programs as potential mechanisms for reducing intimate partner violence in Ghana. They also point to the need to move beyond individual-level interventions and consider community-level programs that empower women to be autonomous.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".