Bibliographic record
Abstract
Vodou is frequently invoked as a cause of Haiti’s continued impoverishment. While scholarly arguments have been advanced for why this is untrue, Vodou is persistently plagued by a poor reputation. This is buttressed, in part, by the frequent appearance in popular culture of the imagined religion of “voodoo.” Vodou and voodoo have entwined destinies, and Vodou will continue to suffer from ill repute as long as voodoo remains an outlet for the expression of racist anxieties. The enduring appeal of voodoo is analyzed through its uses in touristic culture, film, television, and literature. Particular attention is given to the genre of horror movies, in which voodoo’s connections with violence against whites and hypersexuality are exploited to produce both terror and arousal. Le Vodou est souvent invoqué comme une cause de la misère persistante d’Haïti. Bien que les arguments académiques ont été avancés pour prouver le contraire, le Vodou en générale est toujours mal compris et souvent décrié. Les idées erronées du Vodou sont étayées, en partie, par l’utilisation fréquente dans la culture populaire de la religion imaginaire du « voodoo ». Le Vodou et le voodoo possèdent des destins enlacés, et le Vodou continuera à souffrir d’une mauvaise réputation aussi longtemps que le voodoo reste un instrument pour l’expression des anxiétés racistes. L’attrait durable du voodoo est analysé ici à travers ses usages dans la culture touristique, le cinéma, la télévision, et la littérature. Une attention particulière est donnée au genre des films d’horreur, dans lequel les connexions du voodoo avec la violence contre les blancs et l’hypersexualité sont exploitées pour produire, en même temps, la terreur et l’excitation sexuelle.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".