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Record W1998499037 · doi:10.7202/014004ar

Becoming-Other: (Dis)Embodiments of Race in Anne Rice’s Tale of the Body Thief

2006· article· en· W1998499037 on OpenAlexaffvenue
Trevor Holmes

Bibliographic record

VenueRomanticism on the Net · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsVampireHuman sexualityGender studiesEthnic groupRace (biology)White (mutation)Identity (music)PopularitySociologyUndoingAestheticsArtHistoryPsychoanalysisPsychologyLiteratureSocial psychologyAnthropology

Abstract

fetched live from OpenAlex

The vampire/human split in Anne Rice's Vampire Chronicles is structured like a racial split. Becoming a vampire constitutes an essence, a shared material difference that is not something humans can come close to understanding. In the process of erasing actual racial differences through the "Dark Gift," Rice relies on embodiments of ethnicity and racial specificity in her management of gay male desire (a major factor in her popularity). The complexity of the relationships that shift and multiply between desire, race, sexuality and otherness is captured most strikingly in the fourth novel of the series, Tale of the Body Thief. After establishing the gender and sexuality work accomplished by Lestat’s body-switching, the paper examines David Talbot's switch into a young male body himself. Talbot’s own becoming-other, and becoming-vampire thereafter, are instances of both general and specific racialized embodiment. Lestat's experience of the human flesh is different from Talbot's, and in fact does more to constitute identity as gender and sexuality than as race. Talbot's assimilation into Lestat's identity formation (erasing ethnicity by way of becoming an other) still produces a specificity, one that exoticizes a youthful otherness overcoded by Portugal, Africa, India and Brazil. However, the othered body can only be animated by an aging white British gentleman’s mind and manners.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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

Citations1
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueRomanticism on the NetSame topicGothic Literature and Media AnalysisFrench-language works237,207