Associations between Nollywood Movies and Risky Sexual Behaviours among in-School Youths in Nigeria: An Ongoing Study
Bibliographic record
Abstract
Nollywood, the second largest movie industry in the world after America’s Hollywood, is Nigeria’s movie industry. This ongoing study investigates how sexual messages and scenes are communicated to viewers and if there is correlation between the pattern of Nollywood movies exposure and sexual behaviour of in-school adolescents in the southwestern part of Nigeria. Data will be collected from the participants through questionnaire while content of popular Nollywood movies among the participants will be content analyzed. It is expected that this study will provide information about the frequency of sexual scenes and how risky sexual behaviours are portrayed in Nollywood movies. Secondly, it is expected that this study will show the types of relationships that exist between movie exposure behaviour and sexual behaviour in the study population. Nollywood, la deuxième plus grosse industrie du cinéma au monde après Hollywood, est l'industrie du cinéma nigérien. Cet étude en cours examine comment les messages et les scènes à caractères sexuels sont communiquées aux téléspectateurs et s'il existe une corrélation entre le modèle d'exposition aux films Nollywoodiens et les comportements sexuels des adolescents scolarisés dans le sud-ouest du Nigéria. Les données seront collectés auprès des participants par le biais d'un questionnaire et le contenu des films Nollywoodiens populaires auprès des participants sera anlysé. Cette étude devrait fournir des information sur la fréquence des scènes sexuelles et sur la manière dont les comportements sexuels à risque sont décrits dans les films de Nollywood. Il est aussi attendu que cette étude montre les types de relations qui existent entre le comportement d'exposition au cinéma et le comportement sexuel dans la population étudiée.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".