Bibliographic record
Abstract
In 2017, Canada’s Stratford Festival dramatized The Komagata Maru Incident, Sharon Pollock’s play about Canada’s insistence on returning the ship Komagata Maru (KGM) and its passengers to India after it arrived in Vancouver in 1914. This chapter analyzes Pollock’s and Ajmer Rode’s plays about the KGM to examine, within a comparative framework, their differentiated investments in remembering this landmark moment in Canadian history. While Pollock’s play revisits the KGM to critique Canada’s treatment of its minorities, Rode’s play foregrounds the incident to comment on Canadian law in relation to British imperial interests in India, and the historical and ongoing regulation of national borders. Thus, while both plays challenge the official version of the KGM, Rode’s play situates the incident within a broader global history of empire as opposed to Pollock’s national focus on immigration and social exclusion. Nevertheless, by remembering the KGM from the space of time and distance, both plays provide frameworks for investigating colonial policies and attitudes, and for understanding the critical significance of Gurdit Singh’s first-hand account in Voyage of Komagata Maru or India’s Slavery Abroad. By refusing to forget the compelling story of the Komagata Maru journey, the plays function as powerful sites of historical commemoration.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.117 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".