Bibliographic record
Abstract
The paper discusses the problem of international trade in art. The works of art are very specific objects of international trade, because – recognised as cultural goods and part of the national heritage - they are protected against export. Most countries of the world have laws that protect their cultural property. The legal regulations concern different types of the works of art and apply different instruments of art export controls. The paper discusses the import and export of art worldwide. The analysis is based on OECD international trade data Harmonised System 1996 (ITCS International Trade by Commodities Statistics) on the import and export of the works of art (section 97) in the recent years. The relations between export and import are also analysed. On the basis of the collected data it would be possible to identify the countries which have a significant share in the international trade in art. Special attention is given to foreign trade in art in European Community countries as well as in the United States. The UK, France, Germany, the Netherlands, Belgium, Spain and Switzerland are discussed in the European context, while Japan, China, Hong Kong give insights into the Asian environment, with Canada and Mexico representing the Americas and Australia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.002 |
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".