Bibliographic record
Abstract
The commemoration of sacrifice and martyrdom in the Iran–Iraq war led to dissemination of the ‘sacred defence’ culture and its theatre progeny – the Arzeshi genre, which is rooted in Shi’i religious values, Persian culture, and Iranian performance traditions. In response to this, Iranian anti-war theatre practitioners have intervened through a counter-conduct theatricality made up of characters, stories, reasoning, embodied emotions, and scenic languages. A thematic and aesthetic analysis of three stagings of the anti-war play The Whispers Behind the Front Line by the prominent Iranian playwright/director Alirezā Nāderi shows that there has been a shift over two periods of time regarding ‘disguised counter-hegemonic dramaturgy’, alternative characterization, and the ethical engagements of artists with the narrative of war. In this study Marjan Moosavi shows that theatre counter-conducts have shifted since 1995 from a realist aesthetic, reflecting a specific event – the Iran–Iraq war – to a universal, abstract aesthetic practice that sees war as a global phenomenon. Marjan Moosavi is an Iranian-Canadian PhD candidate and instructor at the University of Toronto's Centre for Drama, Theatre, and Performance Studies. She has published articles on Iranian dramaturgy and diasporic theatre in The Routledge Companion to Dramaturgy, TDR, and Critical Stages.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".