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Record W651146712 · doi:10.4000/erea.4475

Theatrical Colours: Cosmetics, Rhetoric and Theatre in Webster’s The White Devil

2015· article· en· W651146712 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueE-rea · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsRhetoricWhite (mutation)Rhetorical questionIronyArtLiteratureCosmeticsPhilosophyLinguistics

Abstract

fetched live from OpenAlex

The paradoxical title of John Webster’s play The White Devil has often led to attempts to identify one of the characters with the titular devil. This paper argues that the difficulties of identification lie not only in the apparent paradox of the association of “white” with “devil”, but also in the changing role of colour in the Jacobean era. This change was marked by the development of painting techniques as well as by the attacks on cosmetics and the “false colouring” (Quintilianus 8, 3, 7) of rhetoric prevalent during this period. Because it combined optical and rhetorical colour, the stage therefore came to be a particularly contentious institution at which similar arguments were often levelled.Through an examination of the three major female characters in The White Devil, Isabella, Zanche and Vittoria, this paper illustrates the way in which these attacks are defused and become the objects of the author’s irony. As females, these characters have a unique relationship with colour because their (alleged) use of cosmetics and thus the authenticity of their skin colour ultimately determines their standing within society. Traditionally, these three characters have been respectively regarded as representatives of a fair Petrarchan heroine, of a black villain inside and out and of a woman occupying a literal grey area. However, this analysis illustrates how powerful a tool these characters’ use of colour in terms of cosmetics, rhetoric and theatre proves to be in determining their roles. Thus, the division into clear-cut colour categories is dissolved which also serves to repudiate the allegations against “artificial colouring” and the theatre, since none of the parties at work in the play emerges as untinged.

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.

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: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.489

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 studies0.0000.000
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 head0.056
GPT teacher head0.247
Teacher spread0.191 · 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