Bibliographic record
Abstract
From Lady Aberdeen, the governor general's wife who wrote of her photographic adventures in Through Canada with a Kodak to Anahareo, Grey Owl's companion who told her side of the story in Devil in Deerskins, from Kootenay historian Clara Graham to Helen MacMurchy, medical doctor and health activist, from the famous pioneering Strickland sisters to the feminist activist and judge Emily Murphy, this compendium of women non-fiction writers is a unique collection.Anne Innis Dagg has produced a wide-ranging and varied collection of individual entries on women whose non-fiction work has been an ever present but often little noticed part of our culture for almost two centuries.This book will prove of great practical use to researchers who wish to use it as an encyclopedia of women's non-fiction writing; its excellent cross-referenced index, which will help the reader find whole groups of women interested in the same subject, from education through immigration to agriculture, is particularly helpful.However, I found its most profound effect came from browsing through the entries without seeking a specific focus.The cumulative effect of reading the entries is to discover a collage of the cultural history of women and their accomplishments in Canada over two centuries.Women in Canada have used a multitude of ways to write themselves into being.In the early days their writing ranged from botany to travel writing to religion.Later, areas such as business, science and politics began to open to them.Each bio-bibliographical entry, even the ones where only limited facts are available, tells the story of a woman reaching out from the private world to which, it would seem, culture has relegated her, to a public world where her particular expertise would have its chance to affirm, shape or change the larger culture.vii
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.585 | 0.501 |
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".