Bibliographic record
Abstract
In 1954, two red faced operas where created in British Columbia by white women: Barbara Pentland’s The Lake imagines the Okanagan from the point of view of Susan Alison, the first white women settler in the region while Lillian Estabrooks and Mary Costley’s Ashnola: A Legend of Sings Water offers a Gilbert and Sullivan cross-dressed version of pre-European contact Aboriginals. This article analyzes these operas and other 1950s texts like newspaper articles and populist histories of British Columbia to demonstrate how invader settlers seek to control the Other semiotically via red face and thus gain a sense of identity that ameliorates their settler status to make them “native.” Red face in these operas betray an imperial sense of melancholy as white women use it to trouble patriarchy while enforcing white privilege. The paper concludes by considering the persistence of neo-colonial red face in the Canadian national imaginary.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.038 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".