CENSORSHIP AND SECURITY: IMPACT OF MEDIA LAWS AND GOVERNMENT ACTIONS ON JOURNALISTS’ SAFETY IN NIGERIA
Bibliographic record
Abstract
Press freedom in Nigeria is facing growing challenges, driven by restrictive media laws, increased government surveillance, and tightening censorship practices. This study explores how these legal and political conditions affect journalists’ safety and limit their ability to work freely. Drawing on survey responses from 21 journalists working in print, broadcast and online media, combined with case studies and policy reviews, the research outlines how censorship is often carried out under the pretext of national security or guiding public interest. Laws such as the Cybercrime Act of 2015, the Nigerian Press Council Act and the National Broadcasting Code are frequently mentioned as tools used to intimidate, detain, or silence journalists, particularly those reporting on sensitive topics like corruption, elections or conflict. Beyond direct government action, the study uncovers how economic pressure and media ownership influence editorial choices. Journalists, whether working in government-owned or privately owned outlets, often face subtle but persistent pressure to support political narratives. One of the most consistent findings is the high level of self-censorship among media professionals, driven by concerns about job loss, legal action or personal safety. Even digital platforms, once considered spaces for free speech, are now being restricted through content takedowns, surveillance and platform bans. The analysis draws on Libertarian, Social Responsibility and Chilling Effect theories to explore the tension between press freedom and state control. These frameworks help explain how fear, regulation and power structures shape journalistic behaviour in complex ways. The study concludes by calling for urgent reforms to protect press freedom in Nigeria, support journalist safety and ensure that media practitioners can operate without fear. It also stresses the need for civil society, global institutions and media allies to actively resist ongoing efforts to suppress free expression.
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 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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".