Revenge Pornography in Nigeria: A Call for Legal Response and Cyber-Censorship of Content by Internet Service Providers
Bibliographic record
Abstract
Abstract Revenge pornography is the online distribution of sexually uncensored images or videos of another person without consent and to cause embarrassment or torment. Victims of revenge pornography suffer significant harm, including losing jobs and, in extreme cases, committing suicide. The public blames the victim for the role they played. Rather than victim-blaming, victims deserve a takedown order and criminal liability for uploaders of such images. This study adopts a doctrinal approach; it examines key statutes and their interpretation by Nigerian courts while juxtaposing it with the law and practice in the United Kingdom. The United Kingdom was undertaken as a case study because it has a developed jurisprudence which can provide lessons for Nigeria. This study found that the current state of laws in Nigeria is ill-equipped to tackle the menace of revenge pornography. The objective of this study is to offer insights on the prevalence of revenge pornography in Nigeria and suggest legal solutions to address this phenomenon. It canvasses for a non-consensual pornography provision that would criminalise the act of revenge pornography in Nigeria. It also makes a case for cyber-censorship of contents by internet service providers and the need for third-party liability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".