MétaCan
Menu
Back to cohort
Record W4412566654 · doi:10.1386/eme_00234_1

Reactionary speech in the digital age

2025· article· en· W4412566654 on OpenAlexafffund
Jason Hannan, Matthew McManus

Bibliographic record

VenueExplorations in Media Ecology · 2025
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversity of Winnipeg
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReactionaryPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

It has been over thirty years since the publication of Albert Hirschman’s The Rhetoric of Reaction. Hirschman’s tripartite model – the perversity, futility and jeopardy theses – offers a powerful lens through which to read the historical corpus of conservative thought. Yet we must ask whether a new model of reactionary rhetoric is needed today, given the very different political atmosphere and media environment from the ones in which Hirschman originally formulated his argument. This article is premised on the view that we urgently require a new conception of reactionary rhetoric. It proposes a different analytical approach from Hirschman’s. First, it adopts a conception of conservatism as a reaction against democracy, a defence of the rich and powerful, and the preservation of hierarchy. Second, it makes a case for incorporating a media-ecological perspective to make sense of reactionary rhetoric. Synthesizing political theory with media ecology, this article proposes that if conservatism is an antidemocratic, antiegalitarian and counterrevolutionary movement, then two central and inevitable elements of conservative rhetoric are denialism and mythmaking. Conservative rhetoric, we propose, has both a negative and an affirmative dimension. The negative dimension consists of (1) the denial of social injustice, (2) the demonization of a wildly exaggerated or completely fictitious enemy and (3) the distortion of the relationship between the powerful and the victims of power. The affirmative dimension consists of (1) the sublimation of populist sentiment, (2) the naturalization of hierarchy and (3) the mythologization of social and political order.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.015
Scholarly communication0.0120.014
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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 designQualitative
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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueExplorations in Media EcologySame topicDigital Communication and LanguageFrench-language works237,207