Multi-level predictors of young people’s attitudes towards gender biases concerning rape, sexual and domestic violence in intimate relationships among young people, Ebonyi State, Southeast Nigeria
Bibliographic record
Abstract
This study assessed multi-level factors that shape young people's attitudes towards gender biases about rape, sexual, and domestic violence in intimate relationships. This cross-sectional study was undertaken in three urban and three rural communities in Ebonyi State, southeast Nigeria. Data were collected from 1,020 young people using an interviewer-administered questionnaire. Descriptive and logistic regression analyses were performed using STATA. Findings revealed that most(64%) young people agree that when a girl doesn't physically fight back, you cannot really say it was rape. Many agreed that a girl who is raped is promiscuous or has a bad reputation (50%) and usually did something careless to put herself in that situation(45%). Young girls were approximately 2 times more likely to have positive attitudes towards sexual violence, rape, and domestic violence in intimate relationships than young boys (OR=1.5;P<0.01). Multi-level strategies to effectively address adverse gender norms and inequalities in intimate relationships are highly recommended.
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 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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".