Decolonizing Curriculum: Teaching the Twenty-First-Century Dramatic Canon
Bibliographic record
Abstract
I have been teaching undergraduate and graduate courses in play-analysis, developmental dramaturgy, adaptation and new play creation for almost two decades. Trained within structural and semiotic approaches to text and performance analysis with emergence of what David Barnett calls “postdramatic theatre texts” (2008:14) and recent calls for decolonizing curriculum, I found myself at a philosophical and theoretical crossroads. This article summarizes my teaching practice and philosophy as inflected through decolonial methods. It argues for our need to teach students to simultaneously position every dramatic text within the critical lens of structural play-analysis and their historical/cultural contextualization or dramaturgical concretization (Vodička 1975). The twenty-first century dramatic texts I teach are often located within the postdramatic European theatre and performance canon (Lehmann 2006), as well as within postcolonial and Indigenous traditions of storytelling. The three plays I chose as my case studies— Arabian Night (2003) by German playwright Roland Schimmelpfennig, Bintou (2002) by Koffi Kwahulé, a Côte d’Ivoire writer living in France, and Burning Vision (2003) by Marie Clements, a Canadian Metis theatre artist—constitute the core of my syllabus for a graduate course in dramaturgy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".