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Record W4395028379 · doi:10.3138/md-67-1-1303

Bertolt Brecht’s “Niobes”: Example, Interruption, and Model

2024· article· en· W4395028379 on OpenAlexvenueno aff
Freddie Rokem

Bibliographic record

VenueModern Drama · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature and Cultural Memory
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryComputer science

Abstract

fetched live from OpenAlex

This article discusses how Bertolt Brecht employed the ancient figure of Niobe as a model for several of his female characters. The examples examined here are his adaptation of Antigone, where the protagonist compares herself to Niobe, as in the classic Sophocles drama; the allusions by Polly Peachum in the Pirate Jenny song in the stage version of The Threepenny Opera; and the dialectical interaction between Mother Courage and her mute daughter Kattrin in Mother Courage and Her Children. Each such “likeness” encompasses a strong emotional involvement or empathy with the Trauer, or sorrow, of the ancient figure of Niobe, who was petrified for boasting of her many children to Leto, and whose offspring then killed all of her children. At the same time, Brecht also allows his characters to resist and even protest against their ancient female role model. On the basis of these examples, the article discusses Brecht’s modern version of the Trauerspiel, based on Walter Benjamin’s ideas; his development of the notion of the model and the model-book with Niobe as a model for the modelling process itself; and, finally, the importance of the notion of the Halt, a stop or interruption, for this modelling process. The article suggests that the close interdependence between Brecht’s oeuvre and the ideas of his close friend Walter Benjamin concerning the Trauerspiel reveals the modelling aspect of many of Brecht’s female characters as well as his multifaceted, critical approach to tragedy.

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)0.001
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.060
GPT teacher head0.259
Teacher spread0.199 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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