Bibliographic record
Abstract
Introduction Alexandra Palmer Fashion Identity *'Very Picturesque and Very Canadian': The Blanket Coat and Anglo-Canadian Identity in the Second Half of the Nineteenth Century ? Eileen Stack* Dressing Up: A Consuming Passion ? Cynthia Cooper* Defrocking Dad: Masculinity and Dress in Montreal, 1700-1867 ? Jan Noel* The Association of Canadian Coutouriers ? Alexandra Palmer Fashion, Trade, and Consumption * Shop and Factory: The Ontario Millinery Trade in Transition, 1870-1930 ? Tina Bates*'The Work Being Chiefly Performed by Women: Female Workers in the Garment Industry in Saint John, New Brunswick, in 1871 ? Peter J. Larocque* Three Thousand Stitches: The Development of the Clothing Industry in Nineteenth-Century Halifax ? M. Elaine Mackay* Enduring Roots: Gibb and Co. and the Nineteenth-Century Tailoring Trade in Montreal ? Gail Cariou* Montreal's Fashion Mile: St Gathering Street, 1890-1930 ? Elizabeth Sifton Fashion and Transition * Dress Reform in Nineteenth-Century Canada ? Barbara E. Kelcey* Fashion and War in Canada, 1939-1945 ? Susan Turnbull Caton* Fashion and Refuge: The Jean Harris Salon, 1941-1961 ? Lydia Ferrabee Sharman Fashion and Journalism * Laced in and Let Down: Women's Fashion Features in the Toronto Daily Press, 1890-1900 ? Barbara M. Freeman* The Fashion of Writing, 1985-2000: Fashion-themed Televisions Impact on the Canadian Fashion Press ? Deborah Pulsang* A Little on the Wild Side: Baton's Prestige Fashion Advertising Published in the Montreal Gazette, 1952-1972 ? Katherine Bosnitch
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.005 |
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".