Bibliographic record
Abstract
Tis book has had a long gestation.Originally, Ravi Malhotra, a legal scholar who focuses on disability rights law with no specialist training in history, read about E.T. Kingsley in Ian McKay's magisterial account of Canadian early-twentieth-century working-class movements, Reasoning Otherwise, one day in 2010.Afer discussions with many historians, he became convinced that Kingsley as a disabled radical was a topic that demanded sustained scholarly attention.With the publication of Michael Oliver's Te Politics of Disablement in 1990, disability studies had taken of, and a book about Kingsley was timely.Yet a trained historian knowledgeable about the period was badly needed to set the project on a frm footing.Tis was particularly true given that Malhotra has always been based in Ottawa, far from the feld of Kingsley's extensive political activities.Malhotra soon identifed Victoria-based Benjamin Isitt as the ideal writing partner.One thing led to another, and we soon found ourselves holding a nearly $70,000 Standard Research Grant from the Social Sciences and Humanities Research Council of Canada.Tis assistance is gratefully acknowledged and enabled us to hire a large interdisciplinary research team that scoured the continent for archives containing references to Kingsley.Afer a long period of research and writing, the book that you hold in your hands emerged.A mini-conference held at the annual meeting of the Canadian Law and Society Association in Winnipeg in June 2014 also helped to crystallize our ideas and increase awareness of Kingsley.We also curated and launched the E.T. Kingsley Historical Archive (www.abletolead.ca), in
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.260 | 0.219 |
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".