Bibliographic record
Abstract
"WHEN A CANADIAN GIRL BECAME AMERICA'S SWEETHEART:" MARY PICKFORD AND QUESTIONS OF NATIONAL IDENTITY DURING THE WWI It is a little known fact that several of the key figures of early American cinema were, in fact, of Canadian extraction. Pioneering writer-director-producer-actor Mack Sennett, for instance, hailed from Richmond, Québec, while May Irwin, famous for providing American cinema with one half of its first onscreen kiss, was originally from Whitby, Ontario. Similarly, each of the first three Academy Award winners for Best Actress also happened to be Canadian-born. (Mary Pickford, born in Toronto, was awarded the first Best Actress Oscar for her performance in Coquette in 1929, to be followed by Montréal native Norma Shearer in 1930 and Cobourg, Ontario's Marie Dressler in 1931). Unlike more obviously foreign, "Other" stars such as Pola Negri and Greta Garbo, these Canadians were, for the most part, physically and linguistically indistinguishable from their...
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.037 | 0.021 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".