The Delivery of Human Rights: Essays in honour of Professor Sir Nigel Rodley
Bibliographic record
Abstract
The Delivery of Human Rights reflects on two overlapping issues in international human rights law: how can existing norms be better implemented and effected, and how can other branches of international law or other international actors be used so as to provide an improved delivery of those norms. Rather than simply looking at the content of the rights, this book will also explore how the framers' intention that individuals benefit from the norms can be achieved. The book is written and published in honour of Professor Sir Nigel Rodley KBE. It celebrates his career as an academic and practitioner in the area of human rights. Professor Rodley acted as the UN Special Rapporteur on Torture from 1993 to 2001 and is currently a member of the UN Human Rights Committee. He is also a member of the International Commission of Jurists. Since 2001 he has been a Member of the UN Human Rights Committee, established under the International Covenant on Civil and Political Rights. In 1998 he was knighted in the Queen's New Year's Honours list for services to Human Rights and International Law and in 2000 he received an honorary LLD from Dalhousie University. He is Professor and Chair of the Human Rights Centre, University of Essex, having taught there since 1990.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".