16. Why has Classical Drama been Foundational for 172 Years at Queen’s University?
Bibliographic record
Abstract
In 2015, Inquiry@Queen’s opened with Classics students performing Aristophanes’ Lysistrata, a 2500-year-old play illuminating themes of gender inequality and the victims of war which resound as strongly with modern audiences as they did with the ancient Greeks. Classical drama’s continuing ability to resonate with contemporary audiences is one of reasons it has long been viewed as a foundational component of a Humanities education. As a project for Queen’s 175th anniversary, the presenter investigated how Classics and other units have incorporated classical drama into Queen’s classes and post-curricular activities since the 1840s. In addition to ancient Greek and Roman plays, the study included plays with classical themes, and post-Classical plays staged by Classics students and professors. The methodology involved data collection from Queen’s Archives, scholarly publications, and other relevant sources. In this poster, I will provide examples to show how classical drama has been used at Queen's in relation to four main goals: its capacity in sustainability ‘and’ inclusivity; its value as a model for development of future cultures; its function as an active learning experience fostered by concentrated and contextualized classical study; and its ability to provide a cultural ‘safe’ space for participants with diverse needs to engage in examination of complex human problems. It is salient that classical drama has continued to be able to adapt to the changing needs of students and educators at Queen’s for at least 172 years.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".