MétaCan
Menu
Back to cohort
Record W4387982670 · doi:10.3138/cjc-2023-0014-en

Mediatizing the COVID-19 Pandemic: International Perspectives

2023· article· en· W4387982670 on OpenAlexaffvenue
Camila Moreira Cesar, Thierry Giasson, David Dumouchel

Bibliographic record

VenueCanadian Journal of Communication · 2023
Typearticle
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyPolitical scienceMedicineInternal medicineInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

Since its outbreak in 2020, the COVID-19 pandemic has upended ways of life all over the world, transforming itself into a medical, social, and political event all at once (Agartan, Cook, & Lin, 2020;Bobba & Hub, 2021; Banque mondiale, 2020).Over the past three years, we have had to learn how to live in an environment reconfigured by the uncertainty resulting from the eruption of a public health crisis of which repercussions have been felt in all areas of social life.In such a context, information and communication flows take on a key role in establishing and highlighting ways of seeing this problem.Such flows, whether they come from private, public, or institutional sources, have proven themselves to be invaluable resources, enabling citizens to cope with challenges posed by an unfamiliar and anxiety-inducing situation.In this sense, informational and communicational processes take part at different levels in the chain of mediations of the social order while increasing social tensions through media processes that are becoming more and more complex.These processes are influenced by a "media logic" (Esser & Strombck, 2014) that contributes to a renewal of norms as well as of organizational modes and habits relative to information and communication.At a time when our societies have become hypermediated, the COVID-19 pandemic has shown how and through what means

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.094
GPT teacher head0.340
Teacher spread0.246 · 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 designNot applicable
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

Explore more

Same venueCanadian Journal of CommunicationSame topicCOVID-19 Digital Contact TracingFrench-language works237,207