Bibliographic record
Abstract
Rare Merit is a beautifully illustrated and astute examination of women photographers in Canada as it took shape in the nineteenth and early-twentieth centuries. Throughout, the camera was both a witness to the colonialism, capitalism, and gendered and racialized social organization, and a protagonist. And women across the country, whether residents or visitors, captured people and places that were entirely new to the lens. This book shows how they did so, and the meaning their work carries. Colleen Skidmore surveys the professional lives and photographs of nearly eighty women – studio portraitists, travel documentarians, photojournalists, fine artists, hobbyists, and photographic printers – from Lucy Maude Montgomery on Prince Edward Island to Élise Livernois in Quebec City, and from Margaret Bourke-White in the Arctic to Hannah Maynard on Vancouver Island. Why women? Why not women? Presenting the exceptional range and impact of their work, Rare Merit proves that women’s practices and images – knowingly omitted from founding narratives of photographic history – were diverse, compelling, widespread, and influential.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.397 | 0.204 |
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".