Antonio Cassese, Five Masters of International Law: Conversations with R.J. Dupuy, E. Jimenez de Arechaga, R. Jennings, L. Henkin and O. Schachter
Bibliographic record
Abstract
This review will comment on Antonio Cassese’s book, entitled Five Masters of International Law: Conversations with R.J. Dupuy, E. Jiménez de Aréchaga, R. Jennings, L. Henkin and O. Schachter. While I was reading this book I was filled with sadness and admiration. Sadness, because I have lost a very dear friend. I will continue to call him Nino in this book review because he would have been surprised and upset if I referred to him otherwise. In some ways Nino’s book reminded me of Fénelon’s Dialogues des morts.1 The difference is that Fénelon’s dialogues are imaginary whereas those contained in Nino’s book are real — but all those who appear in it, the interviewer as well as the interviewees, have now passed away. All the interviews were conducted between 1993 and 1995. By the time Nino had put the interviews together, the five interviewees had died. In his introduction dated September 2010, Nino writes that he ‘is also likely to set out on that eternal voyage soon’.2 This is indeed what he did in October 2011.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.049 | 0.012 |
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".