Becoming-Other: (Dis)Embodiments of Race in Anne Rice’s Tale of the Body Thief
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".