Inconsistent Reports of Sexual Intercourse by Adolescents in Edo State, Nigeria
Bibliographic record
Abstract
Previous research acknowledges the limitations of self-report data on adolescent sexual behaviors. Specifically, the reliability of data on sexual activity collected through survey techniques has been questioned. This paper begins to fill both gaps by analyzing inconsistencies in reporting sexual experience among adolescents in rural communities in Edo State, Nigeria. Longitudinal (panel) data were collected at three annual time points (2009, 2010, and 2011) from adolescents aged 12–17 attending Junior Secondary Schools. Multinomial logistic regression was used to analyze inconsistencies in the reporting of sexual activity between the first two waves. About 26% of the respondents indicated they had not had sex at wave 2 after reporting sexual experience at wave 1 (recanting). Compared with males, females were significantly more likely to recant. Older adolescents were less likely to recant their sexual experiences than younger ones. The study’s findings corroborate previous research questioning the validity of self-report data on adolescent sexual activity and add to calls to find ways to improve data collected from young people on their sexual behaviors, especially for adolescents in rural settings where admitting sexual experience may be highly stigmatized.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".