Research Workshop on Critical Issues in International Refugee Law May 1 and 2, York University
Bibliographic record
Abstract
This paper provides a brief outline and summary of the key academic papers and review commentators’ remarks that were presented at the Research Workshop on Critical Issues in International Refugee Law that was held at York University, Toronto, Canada, May 1 and 2, 2008. One of the principal objectives of this Research Workshop was to bring together some of the world’s leading senior superior and high court judges and legal scholars to examine a limited number of key issues in international refugee law from a number of perspectives, including the jurist/practitioner and theorist/academic viewpoints, with the aim of trying to find the most promising ways forward and/or avenues for further research. Four substantive academic papers were presented by Professors Guy Goodwin-Gill, Oxford University; Jane McAdam, University of New South Wales; Geoff Gilbert, University of Essex; and Kate Jastram, University of California at Berkeley. The Research Workshop keynote address was delivered by the Honourable Justice Albie Sachs, Constitutional Court of South Africa. The Research Workshop also launched a number of wider international collaborative research projects in international refugee law that will be pursued over the next few years.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".