Multigenerational attitudes to gender norms on intimate partner violence and the sexual and reproductive health of young people in Nigeria
Bibliographic record
Abstract
This study undertook an assessment of multigenerational attitudes towards gender norms related to intimate partner violence (IPV), sexuality, and reproductive health behaviours. A cross-sectional household survey was conducted among 1630 young people and adults, in six communities in Ebonyi state, southeast Nigeria. In data analysis, mean attitude scores were computed and compared across generation cohorts using analysis of variance. Attitudes toward each domain of intimate partner relationships served as the dependent variables in three separate linear regression analyses, where the predictors were identified accordingly. The results showed that the differences in mean scores on attitudes towards gender norms about IPV and sexuality in intimate partner relationship were not statistically significant across the generation cohorts (p > 0.05). However, there were significant differences in the attitudes of generation cohorts towards gender norms relating to sexuality and reproductive health behaviour. The sociodemographic predictors of attitudes to gender norms on IPV were male gender (β = 0.106, p = < 0.001) and urban residence (β = 0.075), p = < 0.001), while tertiary education predicted attitudes to gender norms on sexuality (β= - 0.156, p = 0.012) and reproductive health behaviour (β= - 0.216, p = < 0.001). The findings highlighted generational similarities and differences in attitudes towards gender norms in intimate partner relationships. Generational differences were shaped by factors such as age, gender, and education level. Conducting longitudinal studies could reveal how these attitudes evolve and societal changes' impact.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".