Bibliographic record
Abstract
Buttressed by a wealth of new, collaborative research methods and technologies, the contributors of this collection examine women's writing in Canada, past and present, with 11 essays in English and 5 in French. Regenerations was born out of the inaugural conference of the Canadian Writing Research Collaboratory held at the Canadian Literature Centre, University of Alberta, and exemplifies the progress of radically interdisciplinary research, collaboration, and publishing efforts surrounding Canadian women's writing. Researchers and students interested in Canadian literature, Québec literature, women's writing, literary history, feminist theory, and digital humanities scholarship should definitely acquaint themselves with this work. Contributors: Nicole Brossard, Susan Brown, Marie Carrière, Patricia Demers, Louise Dennys, Cinda Gault, Lucie Hotte, Dean Irvine, Gary Kelly, Shauna Lancit, Mary McDonald-Rissanen, Lindsey McMaster, Mary-Jo Romaniuk, Julie Roy, Susan Rudy, Chantal Savoie, Maïté Snauwaert, Rosemary Sullivan, and Sheena Wilson.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.057 | 0.014 |
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".