Bibliographic record
Abstract
This book emerged from the conference "Edging Forward, Acting Up: Gender and Women's History at the Cutting Edge of Scholarship and Social Action." We are grateful to the conference co-chairs, Willeen Keough and Lara Campbell, and to the program chair, Lisa Chilton, for organizing this stimulating conference.The conference was supported by a grant from the Social Sciences and Humanities Research Council of Canada.This grant also aided our work by providing funds for copy-editing this volume and for translating two of the chapters from French to English.Thanks to all the contributors for making our job as editors much easier.You were a wonderful group to work with -enthusiastic, hard-working, and patient.It was especially fun to meet with most of the group for an extra day at the annual meeting of the Canadian Historical Association in Fredericton, New Brunswick.A University of Calgary Faculty of Arts Scholarly Activities Grant provided the funds to support this one-day workshop.Darcy Cullen, at UBC Press, is a marvel.She attended the "Edging Forward" conference, as well as our workshop in Fredericton, and ably ushered us through every aspect of preparing the manuscript.We are grateful for her wise
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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 | 0.002 | 0.007 |
| 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 | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.527 | 0.287 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".