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Record W3208869001

The Plague of Orientalism: Reading Kevin Chong in the Pandemic

2021· article· en· W3208869001 on OpenAlexaffvenueabout
Clint Burnham

Bibliographic record

VenueCanadian literature · 2021
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPlague (disease)PoliticsReading (process)HistoricismPandemicHistoryOrientalismWhite (mutation)CovertImmigrationDemocracyMedia studiesSociologyLiteraturePolitical scienceCoronavirus disease 2019 (COVID-19)LawArtLinguisticsAncient historyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Reading Kevin Chong’s 2018 novel The Plague in the 2020 COVID-19 pandemic, this article argues that historical conditions, including white supremacy in Canada and liberal democratic anxieties regarding same are rendered in the novel both through representative scenes (a political figure visits patients in a pandemic ward, a protest featuring anti-immigrant and anti-racist participants devolves into a riot) and through such speech acts as trigger warnings and land acknowledgments. An intersection of historicist and psychoanalytic interpretations warn against both simply ascribing textual scenes to a literal writing of the Real, and seeking to cordon off the text from the social.

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)0.002
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.623
Threshold uncertainty score0.759

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0290.032
Scholarly communication0.0090.004
Open science0.0010.003
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.290
Teacher spread0.264 · 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
Published2021
Admission routes3
Has abstractyes

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