Bibliographic record
Abstract
From the moment I first came across Jeanne Corbin, in documents seized by the Ontario police, my curiosity was aroused.There were so few women who were politically active and even fewer who were francophones in the Communist Party.This curiosity would have remained unsatisfied were it not for the constant encouragement of Stanley Bréhaut Ryerson, who had known Corbin.Thanks to this politically committed historian, I embarked on an inquiry that should not have taken very long, given that there was apparently little left in the way of documentation about her.The research was, however, long indeed, the documents were numerous, and the study took on a scope that went beyond the figure who had initially prompted it.From the beginning, nothing was quite precise, not even Jeanne Corbin's date of birth.She was said to have been born near Orléans in 1908.It was not until I got hold of her high-school report card, thanks to Lois Rumsey of the Public Schools Archives in Edmonton, that I learned that she had been born in Cellettes, France, in 1906.In the district of Loir-et-Cher, M. André Garneau patiently guided me through the archives of Cellettes and Blois, drew up the Corbin family tree, and showed me the various places Corbin had lived.Without him this invaluable information would have escaped me.The date that the Corbin family emigrated has long been a mystery.From the director of the Blois departmental archives, M. Garneau obtained Jean-Baptiste Corbin's military record, which revealed his 1911 departure.In Tofield, where the Corbins settled, librarian Elizabeth Hubbard visited the cemetery for me and put me in contact with Ronald K. Taylor, who recovered Corbin's school reports and the location of the family's farm.Ron and Mary Taylor very kindly extended me their hospitality and introduced me to Marthe Goubault Tiedemann, a neighbour of the Corbin family.We walked around the farm together Preface
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.576 | 0.382 |
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".