Bibliographic record
Abstract
Whether staged by Émile Fabre (1933) or Jean Meyer (1956) at the Comédie-Française, by Joël Jouanneau in a rather exotic setting in 1987 (Athénée Theatre, Paris), or more recently by Jean Boillot (Poitiers, then on tour, 2004) and Christian Schiaretti (Villeurbanne, 2006) with highly symbolic decor, Coriolanus has served in the twentieth and twenty-first centuries to draw parallels between republican Rome and contemporary social contexts. All these productions, as well as some British ones, such as the most recent version at the New Globe Theatre (2006), and North American ones, such as Robert Lepage’s daring cinematic staging in Québec (1993), triggered harsh criticism from the press. Governments and audiences were not indifferent either – hence, notably, Fabre’s departure from the Comédie-Française in 1934. Even during the Globe’s last season, one could read in The Sunday Times that Coriolanus – with the title-role performed by the athletic Jonathan Cake, who was compared to his counterpart in Mission Impossible – came across as “the most political play ever written by the bard”. Is this phenomenon due to the fact that Shakespeare let the voice of the poor express itself in this play?In this paper, the parallels between the staging of political issues and the responses of the public are discussed in order to address the key question: to what extent do modern directors use Shakespeare’s play as an instrument of social and ideological critique?
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.076 | 0.010 |
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".