Book Review: Torts Tomorrow - a Tribute to John Fleming Edited by Nicholas JMullany and Allen M Linden
Bibliographic record
Abstract
This book was first planned as a way of bringing together various eminent tort scholars in order to honour the late Professor John Fleming (who was then already very ill) for his immense contribution to the field of tort law. The plan was that at least some of the authors of the seventeen essays which are contained in the book would visit Professor Fleming and that they would present these essays to him orally in anticipation of the book's publication. However, Professor Fleming's death, in September 1997, occurred before this plan could be put into effect. The project nevertheless proceeded as a tribute to the great man's impact on the development of modern tort law. In their preface, the editors refer to two particular aspects of Professor Fleming's scholarship. One is that, having been born in Germany, but having spent most of his life living first in Britain, then Australia, and finally the United States (with visits to many other countries), he was firmly of the view that no legal system is inherently superior to any other - a view which was apparent in his comparativist approach to law. The other is that he fervently believed that tort law must constantly evolve to meet the demands of the time and the needs of an ever-changing society. The editors observe in their preface that the essays reflect both these concerns. The contributors are based in countries as diverse as Australia, England, Canada, New Zealand, the United States and Israel, and the essays cover a wide spectrum of torts, many of them relating to new or developing areas of the law.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.055 | 0.030 |
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".