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Record W2992858609 · doi:10.3968/11310

Mass Media, Terrorism and National Security: Defining the Threats

2019· article· en· W2992858609 on OpenAlexvenueno aff
Solomon Samuel Gonina, Linus Mun Ngantem

Bibliographic record

VenueCross-cultural communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsTerrorismNational securityMass mediaGovernment (linguistics)EspionagePublic relationsPolitical scienceBusinessComputer securityInternet privacyLawComputer science

Abstract

fetched live from OpenAlex

The menace of terrorism has been a source of worry to communication specialists. This is more so due to the centrality of communication, particularly the mass media, to the challenge posed by different security concerns, especially national security and terrorism. Violence is escalating rapidly, impacting on local communities, sparking dissensions and eventually, further tensions. Despite being a potent instrument to fighting terrorism and insecurity, this research explores the interface of mass media with security issues, as well as the challenges the media pose to national security, given that the mass media themselves sometimes are a form of threat to the security of nations and their peoples. This study discusses 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 that the mass media industry poses to national security. Terrorist groups including Hezbollah, Hamas and al-Qaeda use computerized gadgets, e-mails and encryptions to support their operations. It is therefore recommended that media professionals must always adhere to their codes of ethics to ensure that they carry out their responsibilities for the ultimate good of society; systems protection and adequate regulation should be given topmost priority by both government and non-governmental bodies; and that citizens should be made to be more aware of the dangers of cyber terrorism as it enables terrorists to operate with a decreased need for government protection. It is also recommended that security operatives should work with media practitioners as watchdogs of the society.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.369
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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