Enacting Civility Through Comic Opera; or, Nation, Race, and Ned McGowan’s War
Bibliographic record
Abstract
Popular historians have frequently described the strange events now known as Ned McGowan’s War in theatrical terms, specifically as comic opera. By taking up June Schlueter’s suggestion that “virtually all” definitions of genre “have rested their case on the ending,” this essay considers how the “generic end” of this comic opera “pointedly involves itself in ideological concerns” by examining the social world that emerges via the climax and denouement of the “War.” Considering the fears of American annexation and occupation that motivated the colonial response to the “War,” its “happy” ending reveals a highly unstable relationship between civil action and national identity at this particular moment. By considering what—and specifically who—fails to be incorporated into the world that emerges at the end of the comic opera, this essay argues that emergent notions of “white civility” in the colony relied on the drawing of and policing of strategic boundaries, in this case along not national but racial lines. The “War” was comprised of social performances which reveal not only the extent to which colonial British Columbia was a “performing society” but also that the boundaries of civil society were negotiated through theatricalized social performances.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.072 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".