Alain-Guy Tachou Sipowo awarded Osgoode Catalyst Fellowship for the 2019-20 academic year
Bibliographic record
Abstract
Alain-Guy Tachou Sipowo will hold the Osgoode Catalyst Fellowship for the 2019-20 academic year.\nSipowo holds a doctorate in law from Laval University (LLD ’14) where he held various positions including research assistant, clinical project supervisor, instructor for the Charles-Rousseau mock trial in international law and lecturer in various disciplines of international law comprising international refugee law, general public international law, international human rights law, and international criminal law.\nHis thesis on the International Criminal Court was awarded the René Cassin Prize of the International Institute for Human Rights in 2015, the special mention of the Michel Robert Prize in International Law of the Canadian Bar Association, Quebec Chapter and the Honorary Award from the Quebec Association of Law Teachers. He has completed a postdoctoral Fellowship funded by the Social Sciences and Humanities Research Council of Canada at McGill’s Centre for Human Rights and Legal Pluralism on the Responsibility of Multinational Corporations for Human Rights Violations Abroad. Sipowo is counsel in the case Immunities and Criminal Proceedings (Equatorial Guinea v. France) before the International Court of Justice. His research and teaching interests include international and transnational law, corporations and human rights, global law and global justice theories.\nThe Osgoode Catalyst Fellowships are designed to bring to Osgoode emerging scholars who have a demonstrated interest in a career in law teaching, and to support and mentor scholars who will enhance the diversity of the profession. Fellows will be given the opportunity to present a faculty seminar with the aim of preparing a major article for publication, to pursue an active affiliation with one of Osgoode’s research centres, and to teach a course at the law school.\nThe Osgoode Catalyst Fellowship announcement was made by Dean Mary Condon on May 24.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.251 | 0.110 |
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".