Bibliographic record
Abstract
The Eighth International Consumer Law Conference was held in Auckland, New Zealand, from 9–11 April 2001. John Skinnon of the Open Polytechnic of New Zealand was instrumental in ensuring that the Conference came to New Zealand on behalf of the International Association for Consumer Law, where it was jointly hosted by the Open Polytechnic and the Research Centre for Business Law at The University of Auckland. It was in large part made possible because of the generous sponsorship of the New Zealand Ministry of Consumer Affairs, the Emily Carpenter Consumer Charitable Trust, Butterworths (NZ), CCH (NZ) and the Open Polytechnic. Over 120 delegates attended from numerous countries, including Argentina, Australia, Belgium, Brazil, Britain, Canada, China, Denmark, Finland, Germany, India, Indonesia, Israel, Italy, Japan, Korea, Macau, Malta, New Zealand, Portugal, Singapore, South Africa, Sweden, Turkey and the United States. The theme was ‘Consumers' Access to Justice'. The essays collected in this volume were chosen from among the sixty papers presented. We thank the authors for their willingness to have their contributions included, and for the enormous patience they have shown during a lengthy editing and pre-publication period. We hope the quality of the final product convinces them that the wait was worthwhile! Words of appreciation only inadequately compensate other people who worked with us on this project. First, Thierry Bourgoignie, President of the International Association for Consumer Law, was most gracious in all his contacts with those who organised and hosted the Conference, and was very helpful throughout.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.406 | 0.197 |
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".