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Record W2079806117 · doi:10.3138/md.2012-0504

Mobilizing Maurya: J.M. Synge, Bertolt Brecht, and the Revolutionary Mother

2013· article· en· W2079806117 on OpenAlexvenueno aff
Susan Cannon Harris

Bibliographic record

VenueModern Drama · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTragedy (event)RealismContext (archaeology)LiteratureHistorySociologyArtLawPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT: Bertolt Brecht’s decision to transform J.M. Synge’s 1904 tragedy Riders to the Sea into a propaganda play about the Spanish Civil War called Señora Carrar’s Rifles (1937) has long baffled scholars, partly because Brecht’s interest in the play cannot be accounted for within an Irish studies paradigm and partly because Riders appears, to most Brecht scholars, to be the antithesis of Brecht’s vision of epic theatre. In this essay, I investigate the circumstances under which Señora Carrar’s Rifles was written and produced to show how and why Brecht came to see Riders to the Sea as a useful model in his ongoing attempt to dramatize the coming to political consciousness of the working-class mother. Considering both the pressures that were forcing Brecht back toward realism and the failure of his attempts to elicit an “epic” performance of his play The Mother from the New York-based Theatre Union in 1935, I argue that Brecht’s engagement with Riders is an attempt to learn from previous mistakes and to put into practice what the Theater Union Mother taught him about staging maternal grief. Riders was useful to Brecht because it showed him how to bring the working-class mother to her radicalizing epiphany within the context of realism and without resorting to the epic and alienating techniques used in The Mother. This reading not only leads us to question standard readings of Maurya’s famous renunciation of grief and mourning at the end of Riders to the Sea but to complicate our understanding of the emotional dynamics of Brechtian epic theatre.

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 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score0.996

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 studies0.0010.001
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 head0.012
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 teacher head, 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

Citations2
Published2013
Admission routes1
Has abstractyes

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