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Record W4250382262 · doi:10.1515/9781474423090

Vampires, Race, and Transnational Hollywoods

2017· book· en· W4250382262 on OpenAlexaboutno aff
Dale Hudson

Bibliographic record

VenueEdinburgh University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRace (biology)Gender studiesSociology

Abstract

fetched live from OpenAlex

A consideration of vampire film production through the lens of transnational cinemaThe figure of the vampire serves as both object and mode of analysis for more than a century of Hollywood filmmaking. Never dying, shifting shape and moving at unnatural speed, as the vampire renews itself by drinking victims' blood, so too does Hollywood renew itself by consuming foreign styles and talent, moving to overseas locations, and proliferating in new guises.In Vampires, Race, and Transnational Hollywoods, Dale Hudson explores the movement of transnational Hollywood's vampires, between low-budget quickies and high-budget franchises, as it appropriates visual styles from German, Mexican and Hong Kong cinemas and off-shores to Canada, Philippines, and South Africa. As the vampire's popularity has swelled, vampire film and television has engaged with changing discourses around race and identity not always addressed in realist modes.Here, teen vampires comfort misunderstood youth, chador-wearing skateboarder vampires promote transnational feminism, African American and Mexican American vampires recover their repressed histories. Looking at contemporary hits like True Blood, Twilight, Underworld and The Strain, classics such as Universal's Dracula and Drácula, and miscegenation melodramas like The Cheat and The Sheik, the book reconfigures Hollywood historiography and tradition as fundamentally transnational, offering fresh interpretations of vampire media as trans-genre sites for political contestation.Read an interview with Dale Hudson on Public AffairsVisit Dale Hudson's website to find out more about his research

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.664
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.253
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2017
Admission routes1
Has abstractyes

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Same venueEdinburgh University Press eBooksSame topicGothic Literature and Media AnalysisFrench-language works237,207