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Record W2402406061 · doi:10.4018/ijt.2016070106

Ethics, Decision-Making, and Risk Communication in the Era of Terroredia

2016· article· en· W2402406061 on OpenAlexaff
Mahmoud M. A. Eid

Bibliographic record

VenueInternational Journal of Technoethics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTerrorismRationalityIslamPublic relationsPolitical scienceState (computer science)Ethical issuesPublic opinionPolitical economyLawSociologyEngineering ethicsEngineeringPoliticsHistoryComputer science

Abstract

fetched live from OpenAlex

Terrorism today is one of the most frequent global severe stress situations. The advanced and widespread new media and information technologies as well as modern tactics of terrorism make the public of any nation in exposure, directly and indirectly, to uncertain potential acts of terrorism. The relationship between terrorists and media personnel has grown widely influential, and has been described recently by the term terroredia, in which the public is the main target of both terrorism and the media. Both responsibility and rationality are fundamental weights for the effectiveness of risk communication during times of terrorism. This paper critically analyzes how policymakers in several Western countries have communicated to the public, through the media, the risk of terrorist attacks by the Islamic State of Iraq and the Levant (ISIL) against their individuals and societies. The study uncovers that rationality and responsibility are lacking in Western media decision-making regarding the risk of ISIL's potential activities.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.397
Teacher spread0.367 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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