Ethnoregional Dynamics of Intimate Partner Violence Against Women in Nigeria
Bibliographic record
Abstract
Intimate partner violence (IPV) is a reality the average Nigerian woman has to grapple with everyday. Ethnicity and place of residence play a pivotal role in the social realities of Nigerian women, especially with their experience of IPV. However, there is a paucity of reviews examining the impact of ethnicity and place of residence on women’s experiences of IPV in Nigeria. This study seeks to explore the ethnoregional dynamics of IPV from the range of studies undertaken on the subject matter. Eighteen studies meant the inclusion criteria for analysis. The major criteria for selecting studies for analysis were peer-reviewed studies on IPV against women and studies on a Nigerian population, regardless of the nationality of the authors. Databases like the University of Saskatchewan Library , ProQuest , Sociological Abstracts , and Journal Storage ( JSTOR) were used in searching for peer-reviewed studies. The study revealed that Igbo women tend to experience IPV more than Yoruba and Hausa women. The study also found that rural women tend to experience IPV more than urban women. The study points out some of the services available for female victims of IPV and the possible strategies that can be adapted to reach them effectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 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".