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Record W4410452356 · doi:10.51698/tripodos.2025.57.07

Comparison of COVID-19 discourse in conservatives and liberals: The case of Canada, the United States, the United Kingdom, France, Germany, and Spain

2025· article· en· W4410452356 on OpenAlex
J. Pedro Marfil Medina, María Hernández-Herrarte, Patricia Zamora-Martínez

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTripodos · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCommunication and COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsKingdomCoronavirus disease 2019 (COVID-19)Political science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Economic historyHistoryVirologyMedicineOutbreak

Abstract

fetched live from OpenAlex

In March 2020, the COVID-19 crisis triggered a worldwide adoption of extraordinary measures to contain the disease, forcing current political actors to use both digital channels and traditional media to cross borders and get their messages across to the public about preventive measures and the impact of the situation. The research uses content analysis to examine the communication and discursive strategy of the leaders of Canada, the United States, the United Kingdom, France, Germany and Spain within their messages announcing the state of alarm. The results point to the existence of narrative styles in the interventions of politicians involved, clearly identifiable on the left-right axis, as well as the use of common resources that seek cohesion and citizen awareness at a time of great difficulty for those countries they represent.

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.087
GPT teacher head0.436
Teacher spread0.349 · 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