MétaCan
Menu
Back to cohort
Record W2079509499 · doi:10.3138/md.2012-0448

“These Noxious Microbes”: Pathological Dramaturgy in George Bernard Shaw’s<i>Too True to Be Good</i>

2013· article· en· W2079509499 on OpenAlexvenueno aff
Christopher Wixson

Bibliographic record

VenueModern Drama · 2013
Typearticle
Languageen
FieldMedicine
TopicLiterature Analysis and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)Privilege (computing)DramaturgyHistoryArtEliteLiteratureAestheticsArt historySociologyPsychoanalysisLawPsychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

ABSTRACT: This essay charts the interdependency of form and content in Bernard Shaw’s Too True to Be Good (1931). In this late play, the playwright, building upon his well-known attacks against medical theory and practice, views class privilege, colonial relations, and dramatic structure itself through the lens of disease. Angrily taking the stage in act one, the unusual, acerbic Microbe inaugurates Shaw’s dissection of imperialist discourse and attempt to purge the theatrical textual body of its pathogenic conventions.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.040
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.251
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueModern DramaSame topicLiterature Analysis and CriticismFrench-language works237,207