The Menace of Domestic Violence: Improving the Lives of Women in Nigeria
Bibliographic record
Abstract
The scourge of domestic violence as well as other forms of violence against women has eaten deep into the fabric of our society creating a lopsided gender balance with the female gender being the greatest victim. Violence has taken different forms ranging from sexual to physical and psychological as well as other forms. This degrades the humanity of the woman in our society. Abusive partners and perpetrators base their actions on superior nature of the male sex, religion, law, custom, economic situation, family pressure, and their behavioural pattern. It is believed that lack of a legal framework universally enforced as well as lack of trained law enforcement officers promotes the violence of women in Nigeria. A proactive legal framework, establishment of confidential and well equipped family courts, training of law enforcement officers, shelters and counselling centres can reduce the abuse of women in Nigeria and across the globe. The physical, sociological and psychological effect of violence against women is unquantifiable. To achieve a fair and balanced society, women must be valued, respected and supported and not battered either by stick or word of mouth.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".