William Beckford’s Comic Book, or Visualizing Orientalism with <i>Vathek</i>
Bibliographic record
Abstract
Since its publication in 1786, William Beckford’s oriental tale Vathek has polarized readers. Written in the style of The Arabian Nights, Beckford’s novella of the ninth caliph of Baghdad has been paradoxically defined as Eastern fable, Western fiction, autobiography, biography, and proto-ethnography. Likewise, stylistic assessments have cast Beckford’s tale as satire, parody, pastiche, gothic, horror, and camp. This article attributes Vathek’s striking polysemy to its visualizing orientalism, a graphic—and graphical—manner of depiction not unlike the visual-textual language of comics. With its emphasis on setting, action, and gesture, Vathek reads like a classic action-adventure comic book. Moreover, Beckford’s penchant for exaggeration and distortion steers Vathek into the domain of caricature and cartooning, an aesthetic that dominated the most popular European action-adventure comics, or bandes dessinées, of the mid-twentieth century. Drawing heavily on comics theory, this anachronistic and experimental re-evaluation of Vathek as a comic book uncovers the mechanics of Beckford’s visualizing orientalism and gauges the effects of caricature and cartoons on its resonance and reception.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".