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Record W4292879210 · doi:10.1177/00027642221118265

From “Angry Mobs” to “Citizens in Anguish”: The Malleability of the Protest Paradigm in the International News Coverage of the 2021 US Capitol Attack

2022· article· en· W4292879210 on OpenAlexaboutno aff
Volha Kananovich

Bibliographic record

VenueAmerican Behavioral Scientist · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsAuthoritarianismLegitimacyFraming (construction)Political economyPoliticsGeopoliticsIdeologySociologyDemocracyPolitical scienceChinaMedia studiesLawHistory

Abstract

fetched live from OpenAlex

This study tests the robustness of the “protest paradigm”—a routinized, predominantly negative pattern in covering social protest—by examining the news coverage of the 2021 US Capitol attack in eight countries that vary in the nature of their political regime and geopolitical standing, with democratic US allies United Kingdom, Canada, Germany, France, Australia on one side, and authoritarian adversaries Russia, China, and Iran on the other. Based on a computer-assisted analysis of 3,579 news articles, the study shows that rather than operating as a rigid template, the protest paradigm offers national media a malleable set of journalistic devices that can be appropriated to construct the meaning of disruptive global events in a way that reproduces dominant domestic ideologies and advances the ruling elites’ geopolitical interests. In addition to theoretical contribution, the study offers a novel empirical finding to the literature on protest coverage by providing evidence of national media not simply deviating from, but explicitly violating the protest paradigm. As demonstrated by the analysis of the Russian press, rather than delegitimizing the January 6 attackers by making light of their agenda and emphasizing their unruly behavior—which could be expected from coverage consistent with the protest paradigm—the Russian state-owned media trivialized the brutality of the attack by opting for cues with less violent connotations and elevated the legitimacy of the protesters’ actions by framing them as valid demands by politically minded citizens unjustly prosecuted for concerns about the integrity of electoral process.

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)0.000
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 score0.048
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.038
GPT teacher head0.349
Teacher spread0.312 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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