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Record W2321954827 · doi:10.1386/host.2.2.217_1

Hybrid vigour: Heterogeneity, horror and history in George R. R. Martin’s Fevre Dream

2011· article· en· W2321954827 on OpenAlexaff
Jonathan Newell

Bibliographic record

VenueHorror Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDreamMonsterNarrativeGeorge (robot)VampireZeitgeistLiteratureArtAestheticsPhilosophyPsychoanalysisSociologyArt historyEpistemologyPsychology

Abstract

fetched live from OpenAlex

Equal parts antebellum steamboat odyssey and gothic vampire story, Fevre Dream (1982) is a consciously hybrid novel, one that embodies, encompasses and ultimately transcends multiple genres. My article uses Monster Theory – especially Nina Auerbach’s theory that vampires tend to personify a historical Zeitgeist – to deconstruct the generic play of Fevre Dream, demonstrating that the novel’s hybridism, rather than undermining aesthetic unity of effect, in fact engenders its success both as a historical novel and a tale of terror. In doing so the article not only interrogates the rigidity of generic boundaries but shows how the horrific specifically can complement rather than contaminate an otherwise realistic historical narrative.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.018
Scholarly communication0.0060.004
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.313
Teacher spread0.237 · 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
Published2011
Admission routes1
Has abstractyes

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