Bibliographic record
Abstract
This volume of essays seeks to honour a remarkable, true renaissance man, Justice Florentino P. Feliciano. We are privileged to know him as a jurist, a teacher, a scholar, a lawyer, a loyal citizen of his beloved country, the Philippines, and a citizen of the world. He has had multiple careers of achievement and positive legacy in so many fields that it is hard to imagine how one individual could accomplish it all. He was a Justice of the Philippines Supreme Court from 1986 to 1995, thereafter, he was one of the first seven members of the World Trade Organization's Appellate Body from 1995 to 2001 and its Chairman in 2000 to 2001. For years he has been one of the world's most experienced international legal scholars and arbitrators. He is highly respected in the international law community having been, among many other distinctions, an associé de l'Institut de Droit International for almost forty years and a Member of the Curatorium of the Hague Academy of International Law. A short biographical note on Justice Feliciano and a bibliography of his publications is included in this volume. Justice Feliciano (‘Toy’ to his many friends and colleagues around the world) is a very humble, kind and thoughtful gentleman. He is a principled and religious man, with a passion for justice, equality, and the rule of law, both in his own country and in the international community.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.428 | 0.245 |
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".