Professors Poonam Puri and Obiora Okafor Receive 2016-17 Harry Arthurs Collaborative Research Grants
Bibliographic record
Abstract
The Harry Arthurs Fund (named after Professor Emeritus Harry Arthurs) is intended to encourage and enhance the intellectual life at Osgoode by promoting collaborative scholarly endeavours. The recipients of the 2016-17 Harry Arthurs Collaborative Research Grants are:\nProfessor Poonam Puri \n“The award will fund “Of Efficiency, Certainty, Protection & Fairness: A Reading Group on Future Directions in Business in Law in Canada.” The project will involve several group meetings on selected topics in business law. The group will include, but not be limited to, colleagues in the business law area. The project will involve discussing our own research, discussing the research of invited scholars, and/or discussing a selected reading for the session. A small number of graduate students and/or JD students may be invited. The reading group will allow us to cross-fertilize, think laterally under the broad banner of business law, and hopefully inspire new ideas and further collaborative research.”\nProfessor Obiora Okafor \n“The award will fund a Third World Approaches to International Law (TWAIL) seminar/discussion group series, and facilitate close academic engagement between the collaborating Osgoodeafaculty and non-Osgoode scholars. The substantive focus of the series is on the latest currents in and applications of Third World Approaches to International Law theory and praxis. The series brings to Osgoode and York about three to five emerging or established scholars who work within, or engage in some way, the TWAIL movement in international law scholarship, and who will catalyze the anticipated discussion sessions/seminars.”
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.345 | 0.187 |
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".