Bibliographic record
Abstract
Abstract Taking public interest into consideration before imposing anti-dumping measures is not a requirement contained in the GATT 1947 or the WTO Anti-dumping Agreement. Some GATT signatories like Australia and Canada occasionally refer to public interest but only the Community systematically applies a Community interest test before any measures are adopted. Community interest was one of the central points of discussion when the Community’s anti-dumping law was reformed in 1994 to reflect the results of the Uruguay Round. The provisions on Community interest contained in Basic Regulation 384/96 are more elaborate than the corresponding provisions of Article 11(1) and 12(1) of Basic Regulation 2423/88. An important innovation can be noted with regard to procedural provisions. The degree of detail in which the procedural rights and obligations are set out in Article 21 emphasizes the need for Community Institutions to have at their disposal more comprehensive information than under Basic Regulation 2423/88 when determining the question of Community interest. The new rules have also considerably clarified the analytical framework. Therefore, the Community interest analysis relating to investigations which have been carried out under the old Basic Regulation, can today only serve to a limited extent as guidance.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.012 |
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".