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Record W4410419262 · doi:10.1136/medhum-2024-013193

Pandemics and the gothic, then and now: a hum in the background

2025· article· en· W4410419262 on OpenAlexafffund
Julia M. Wright

Bibliographic record

VenueMedical Humanities · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHumPandemicHistoryCoronavirus disease 2019 (COVID-19)Art historyMedicinePathology

Abstract

fetched live from OpenAlex

While the assertion, ‘no one really wants to talk about COVID anymore’, has become a common refrain, cultural evidence suggests otherwise. Rather, cultural materials indicate not only a sustained interest in epidemic and pandemic experiences in the past but also continuing interest in our own pandemic era. However, this interest is often registered through gestures and brief mentions rather than explicit and sustained plague narratives. This paper considers these trends, especially in Gothic works, a literary tradition rooted in hyperbolic representations of threats that also represents disease on frank terms consistent with current medical knowledge. Pandemics appear in Gothic writing two centuries ago through brief references that suggest the daily experience of danger. Pandemic-era television is following the same strategies. Like ‘fevers’ and ‘plagues’ in the early 1800s, COVID-19 can be raised briefly and often indirectly. There is also attention to other aspects of the pandemic, including isolation and misinformation. In the popular Gothic series, Interview with the Vampire (2022–), ‘plague’ and misinformation are captured on terms drawn from earlier Gothic writing and intertwined to reflect on the misinformation of the COVID-19 era.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.064
GPT teacher head0.277
Teacher spread0.213 · 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
Published2025
Admission routes2
Has abstractyes

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