Introduction to Volume 12, 2009
Bibliographic record
Abstract
With this issue, the Journal of International Economic Law launches its 12th volume in its 12th year of publication. Time certainly does pass quickly, since the original issue and volume of this Journal seems only a recent event! In this first issue of the 12th volume of the Journal, readers will find the now traditional opening essay embodying some personal perspectives of a leading scholar. This year, Professor Thomas Cottier, Professor of European and International Economic Law, Director of the World Trade Institute and the National Centre of Competence in Research NCCR–Trade Regulation, University of Bern, Switzerland, authors that essay reflecting among other subjects on the future of international economic law. Professor Cottier's essay is followed by a number of stimulating articles on varied subjects including trade versus culture in the digital environment, export credit support under the SCM agreement, Canada's litigation experience in Lumber IV and necessity exceptions in WTO Law through the lens of the retreaded Tyres case. This issue also features the now traditional series of short surveys, including indexes, statistical information on dispute settlement and bibliography overviews that should be very useful to readers.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.420 | 0.344 |
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".