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Record W2324238192 · doi:10.1177/1748048516640202

Circulating health rumors in the ‘Arab World’: A 12-month content analysis of news stories and reader commentary about Middle East Respiratory Syndrome from two Middle Eastern news outlets

2016· article· en· W2324238192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Communication Gazette · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsFraming (construction)Middle East respiratory syndromeMiddle EastRumorMedia studiesPrivilege (computing)EntertainmentNews mediaThe InternetSpeculationHistoryAdvertisingPolitical scienceCoronavirus disease 2019 (COVID-19)SociologyMedicinePublic relationsComputer scienceLawBusinessInfectious disease (medical specialty)World Wide WebDisease

Abstract

fetched live from OpenAlex

The Internet provides great opportunity for news as well as entertainment. One such use is to keep abreast of public health concerns. As news outlets’ websites give the audience the privilege of interacting and posting comments as an ‘anonymous user’ following the posted story, these initial comments trigger further comments—which can lead to speculation, rumor, and inaccurate information. The purpose of the current study was to compare one year of news and comments about the outbreak of Middle Eastern Respiratory Syndrome from two major Middle Eastern online news outlets from June 2013 to June 2014. All stories and reader comments about this topic were collected from Al Jazeera and Al-Arabiya and reviewed using framing analysis to determine their framing and approach to the outbreak. The research focused primarily on how discussion and rumor may spread through both the stories as well as the controversial commentary sections.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.947

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.198
GPT teacher head0.356
Teacher spread0.158 · 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