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Record W4406970364 · doi:10.3138/utq.93.04.04

Viral Monsters: Reimagining the Zombie after COVID-19

2024· article· en· W4406970364 on OpenAlexvenueno aff
Dragoslav Momcilovic

Bibliographic record

VenueUniversity of Toronto Quarterly · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsZombieCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicVirologyHistoryArtComputer scienceComputer securityMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

This article reframes the contemporary zombie as a viral monster that unveils and recreates certain aspects of the inconsistent and disruptive workings of COVID-19 and other global pandemics, both real and imagined. This viral idiom, which implicates even modern archetypal zombie narratives like George A. Romero’s genre-defining horror film Night of the Living Dead from 1968, amplifies the classic ontological ambivalence of the zombie as it lumbers in a murky liminal space between life and death, familiarity and abjection, form and chaos. But, in the age of COVID-19, the zombie-virus composite mobilizes and intensifies many of the cultural anxieties and ideological clashes that the current global pandemic goes on to provoke. This is particularly true, and even more troubling, in recent zombie television franchises that offer more sustained visions of long-term suffering and traumatic adaptation in a world irreversibly changed by such viral monsters. To this end, this article offers close readings of one of the most popular incarnations of the viral zombie appearing in recent cultural memory, the so-called “walkers” of The Walking Dead television franchise, whose production and storytelling mechanisms in its final season have been shaped in large part by COVID-19 safety protocols. This article argues that the viral monsters of The Walking Dead television series incarnate a unique and timely iteration of the global outbreak narrative, one that detaches itself from the lingering hope of containment and restoration of an older order and links it instead to ongoing crisis and uncertain futures such as those that accompany what we might call the culture of COVID-19 and its contested concerns about risk, protection, politicization, and power.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0190.024
Scholarly communication0.0110.009
Open science0.0010.011
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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 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
Published2024
Admission routes1
Has abstractyes

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