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Record W4309851914 · doi:10.32920/24612849.v1

Journalistic Role Performance in Times of COVID

2023· article· en· W4309851914 on OpenAlexafffund
Daniel C. Hallin, Claudia Mellado, Akiba A. Cohen, Nicolas Hubé, David Nolan, Gabriella Szabó, Yasser Abuali, Carlos Arcila Calderón, Maha Abdulmajeed Attia, Nicole Blanchett, Katherine Chen, Sergey Davydov, Mariana De Maio, Miguel Garcés-Prettel, Marju Himma-Kadakas, María Luisa Humanes, Christi I-Hsuan Lin, Sophie Lecheler, Misook Lee, Mireya Márquez-Ramírez, Jamie Matthews, Karen McIntyre, Jad Melki, Peter Maurer, Marco Mazzoni, Jacques Mick, Kristina Milić, Fergal Quinn, Terje Skjerdal, Agnieszka Stępińska, Sarah Van Leuven, Diana Viveros, Vinzenz Wyss, Natalia Ybáñez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsToronto Metropolitan University
FundersEuropean Regional Development FundDirectorate-General for Justice and ConsumersCarter G. Woodson Institute for African-American and African Studies, University of VirginiaCalifornia Center for Population Research, University of California, Los AngelesNemzeti Kutatási Fejlesztési és Innovációs HivatalMinistério da Agricultura, do Mar, do Ambiente e do Ordenamento do TerritórioPontificia Universidad Católica de ValparaísoMitacsSanming Project of Medicine in ShenzhenUniversidad Autónoma MetropolitanaDepartment of Sport and Recreation, Northern Territory GovernmentDirectorate-General for International Cooperation and DevelopmentCommonwealth Scientific and Industrial Research OrganisationUniversidad Nacional del Centro de la Provincia de Buenos AiresMinisterio de Economía y CompetitividadVirginia Agricultural Experiment Station, Virginia Polytechnic Institute and State UniversityToronto General and Western Hospital FoundationSan Diego Area Law LibrariesUniversidad Iberoamericana Ciudad de México
KeywordsNewspaperDeferenceJournalismPerspective (graphical)Political sciencePoliticsCoronavirus disease 2019 (COVID-19)Crisis communicationPublic relationsNews mediaMedia studiesSociologyLawMedicine

Abstract

fetched live from OpenAlex

This paper examines journalistic role performance in coverage of the COVID-19 pandemic, based on a content analysis of newspaper, television, radio and online news in 37 countries. We test a set of hypotheses derived from two perspectives on the role of journalism in health crises. Mediatization theories assume that news media tend to sensationalize or to politicize health crises. A contrasting perspective holds that journalists shift toward more deferential and cooperative stances toward health and political authorities in a health crisis, attempting to mobilize the public to act according to the best science. Hypotheses derived from these perspectives are tested using the standard measures of journalistic roles developed by the Journalistic Role Performance Project. Results show that the deference/cooperation/consensus perspective is better supported, with media moving away from the Watchdog and Infotainment, and toward performance of the Service and Civic roles. We also explore differences in the pattern by country.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0030.004
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.336
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes2
Has abstractyes

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