Women’s Status among Households in Southern Ethiopia: Survey of Autonomy and Power
Bibliographic record
Abstract
Abstract This study examined two key dimensions of women’s status (autonomy and intimate partners violence) in Southern Nations, Nationalities and Peoples Region (SNNPR) of Ethiopia based on regional data collected from five randomly selected zones and one city administration; namely, Sidama, Hadya, Gamo Gofa, South Omo, Bench Maji and Hawassa City Administration. The analysis revealed that while joint decision is fairly high, women’s independent decision making on key household domains is generally low. Significant proportions of women in the region are exposed to violence by their partners ranging from insult to heavy physical injury. The fact that nearly half of the women experienced insult and close to a quarter of them faced beating is indicative of the low status of women in society. The regression analysis indicated that seven variables determine the occurrence of violent acts against women in the study area, namely household size, education, access to radio, value of children index, wealth index and level of women autonomy. On the other hand, decision making autonomy is affected by wealth status, household size, access to radio and sex preference index. Finally, the study highlighted the importance of addressing the limited technical and operational capacities to implement gender policy and legal frameworks effectively and efficiently.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".