Defining Mass Media’s Threats to National Security
Bibliographic record
Abstract
Violence is escalating rapidly, impacting on local communities, sparking dissensions and eventually, further tensions. The mass media, despite being a potent instrument to fighting terrorism and insecurity, also pose their own kind of challenges to national security, given that the mass media themselves sometimes are a form of threat to the security of nations and their peoples. Hinged on the Boomerang Effect theory, this study uses the Narrative Analysis methodology to discuss the role mass media play in the business of human security versus national security. It identifies espionage, propaganda, cultural imperialism, regulatory concerns, editorial manipulations, as well as the Internet as some of the threats. Terrorist groups including Islamic State in Syril, Islamic State in West Africa (ISWA), Boko Haram, Hamas and al-Qaeda use mediatised gadgets, e-mails and encryptions to support their operations. It is therefore recommended that media professionals must ensure systems protection and adequate regulation as well as adhere to their codes of ethics to ensure that they carry out their responsibilities for the ultimate good of society.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.006 |
| 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".