Congratulations to Arnup Cup Winners (& third-year JD students) Bessmah Hamed and Rachel Devon
Bibliographic record
Abstract
WeirFoulds is proud to continue to sponsor the Arnup Cup, an annual trial advocacy competition for Ontario law schools, organized by The Advocates' Society. The Cup bears the name of the Honourable John D. Arnup, O.C., Q.C., who for many years sat as a distinguished member of the Court of Appeal for Ontario following a career at WeirFoulds as one of Canada's finest litigation counsel.\nTeams from each of Ontario's law schools participate in the Toronto held trials to vie for the right to represent the province in Canada's national trial advocacy competition, the prestigious Sopinka Cup. The moot was presided over by Mr. Justice Clayton Conlan of the Superior Court of Justice, with senior members of The Advocates' Society acting as assessors, including WeirFoulds partners John M. Buhlman, Chair of the Arnup Cup committee and assessor, and Marie-Andrée Vermette and J. Gregory Richards.\nThe continued sponsorship of the Arnup Cup is another example of how WeirFoulds is committed to the continued growth and pursuit of excellence in the legal industry. We congratulate the winners this year, and look forward to another exciting competition in 2018.\nWinner: Osgoode Hall Law School Bessmah Hamed and Rachel Devon\nSecond Place: Queen's University Hamish Mills-McEwan and Jordan Kirlik\nTo learn more about the Arnup Cup competition, please visit The Advocates' Society website.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.152 | 0.066 |
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".