Book Reviews
Bibliographic record
Abstract
Books reviewed: The Law of Energy for Sustainable Development, edited by Adrian J. Bradbrook, Rosemary Lyster, Richard Ottinger and Wang Xi, published by Cambridge University Press, 2005, 630pp, £75.00, hardback. Fresh Water and International Economic Law, edited by Edith Brown Weiss, Laurence Boisson de Chazournes and Nathalie Bernasconi-Osterwalder, published by Oxford University Press, 2005, 506pp, £70.00, hardback. Handbook of Global Environmental Politics, edited by Peter Dauvergne, published by Edward Elgar, 2005, 560pp, £125.00, hardback. Emerging Forces in Environmental Governance, edited by Norichika Kanie and Peter M. Haas, published by United Nations University Press, 2004, 320pp, US$36.00, paperback. Economic Globalization and Compliance with International Environmental Agreements edited by Alexandre Kiss, Dinah Shelton and Kanami Ishibashi, published by Kluwer Law International, 2003, 352pp, £85.00, hardback. German Environmental Law for Practitioners, edited by Horst Schlemminger and Claus-Peter Martens, 2nd edition, published by Kluwer Law International, 2004, 833pp, £119.25, hardback. The International Climate Change Regime: A Guide to Rules, Institutions and Procedures, Farhana Yamin and Joanna Depledge, published by Cambridge University Press, 2004, 730pp, £40.00, paperback.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.599 | 0.564 |
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".