A Comparative Analysis of the Response of the UNHCR and Industrialized States to Rapidly Fluctuating Refugee Status and Asylum Applications: Lessons and Best Practices for RSD Systems Design and Administration
Bibliographic record
Abstract
Journal Article A Comparative Analysis of the Response of the UNHCR and Industrialized States to Rapidly Fluctuating Refugee Status and Asylum Applications: Lessons and Best Practices for RSD Systems Design and Administration Get access James C. Simeon James C. Simeon * *James C. Simeon, PhD, Assistant Professor, School of Public Policy and Administration, Faculty of Liberal Arts and Professional Studies, and Centre for Refugee Studies, York University, Toronto, Ontario, Canada. This article was originally presented as a paper at the International Association for the Study of Forced Migration (IASFM) 12th International Conference, 'Transforming Boundaries', University of Nicosia, Cyprus, 28 June - 2 July 2009. I should like to thank all those who provided comments on earlier drafts of the paper, including, Matthew Albert, Samuel Cheung, Kate Jastram, Susan McGrath, Michele Millard and Lori Scialabba. I should also like to thank the Journal's anonymous reviewers for their helpful suggestions, which I have tried to incorporate. The law is stated as at July 2009. Author email address: jcsimeon@yorku.ca Search for other works by this author on: Oxford Academic Google Scholar International Journal of Refugee Law, Volume 22, Issue 1, March 2010, Pages 72–103, https://doi.org/10.1093/ijrl/eeq001 Published: 10 February 2010
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".