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Record W4404232838 · doi:10.3389/fcomm.2024.1461250

“Pageantry of aggression”: QAnon, animality, and the violent pursuit of whiteness

2024· article· en· W4404232838 on OpenAlexaff
Lauren Corman

Bibliographic record

VenueFrontiers in Communication · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsBrock University
Fundersnot available
KeywordsAggressionChemistryPsychologySocial psychology

Abstract

fetched live from OpenAlex

While the specifics of the far-right COVID-denying QAnon movement may remain cloudy within popular consciousness, in contrast, many can easily conjure the image of Jacob Chansley, the so-called “QAnon Shaman,” when evoking the January 6th US Capitol riot. Chansley, face-painted in the American flag and draped in faux regalia—a virtual menagerie of animals: coyote, buffalo, and eagle—appears clearly, spear in hand, as if parting the fog of war. Photos of Chansley howling or brazenly posing on the Senate dais are indelibly sketched into our collective memory. Some may conjure him simply as a buffoon, but his trespassing and seditious antics are interwoven with a costume that pulls at the long thread of European and American colonialism. This article posits that Chansley’s animalized insurrectionist attire and his ability to play at the borderlands between human and animal, civilized and uncivilized, was an enactment of white supremacy. Insulated by conjoined racist and speciesist legacies, his ensemble placed him closer not only to Western constructions of nature, but also to animality, all without threatening his human status. Working at the intersections of critical race theory and critical animal studies, and illustrated with mainstream news accounts, this article considers broader cultural contexts that reveal Chansley’s sartorial representation as anything but benign.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.326
Teacher spread0.308 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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