Bibliographic record
Abstract
However many hours are spent in solitary study and composition, scholarship is an essentially collaborative art.My debt begins with Lee Gibson, who introduced me to the joys of probing the past, and with whom my early historical research and writing were shared.It was Judge Roy St George Stubbs, who laboured long and almost alone at first on the barren plains of western Canadian legal history, who introduced me to the Quarterly Court of Assiniboia and some of the unforgettable people who sat on its bench and in its dock and witness box.Leslie Hoffman was the first person to begin work on the current project -back in 1990-93 -by transcribing volumes A, B, and C of the court records in electronic form.When volume D was recently discovered, Leslie agreed to transcribe that also, and did so with remarkable dispatch.Her contribution -astonishingly accurate given that she was working from photocopies of microfilm the first time and from amateur photographs the second -is the bedrock of this book, and I am deeply indebted to her.A change of residence, and of professional preoccupations, necessitated my putting the project aside even before Leslie had finished transcribing the first three volumes.When I was finally able, a few years ago, to turn my attention to the quarterly courts once more, I was heartily encouraged to do so by Dr DeLloyd Guth, director of the Legal History Project in the Faculty of Law at the University of Manitoba, in whose custody the transcripts had remained.And DeLloyd did much more than offer encouragement.It was he who proposed a collaboration between the Faculty of Law and the Centre for Rupert's Land Studies at the University of Winnipeg, and he and his assistant Sue Law provided much other practical help in the early stages of the revived project.DeLloyd
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.343 | 0.254 |
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".