Handbook on the Law of Cultural Heritage and International Trade
Bibliographic record
Abstract
Contents: Cultural Heritage Law James A.R. Nafziger and Robert Kirkwood Paterson 1. International Trade in Cultural Material James A.R. Nafziger and Robert Kirkwood Paterson 2. Australia Craig Forrest 3. Canada Robert Kirkwood Paterson 4. China James Ding 5. France Marie Cornu 6. Germany Kurt Siehr 7. Greece Elina N. Moustaira 8. Ireland Patricia Conlan 9. Israel Talia Einhorn 10. Italy Manlio Frigo 11. Japan Shigeru Kozai and Toshiyuki Kono 12. Mexico Ernesto Becerril 13. New Zealand Piers Davies and Paul Myburgh 14. Poland Andrzej Jakubowski and Olgierd Jakubowski 15. South Africa Margaret Beukes 16. Sweden Thomas Adlercreutz 17. Switzerland Marc-Andre Renold and Beat Schonenberger 18. Turkey Janet Blake 19. United Kingdom Kevin Chamberlain and Kristin Hausler 20. United States James A.R. Nafziger 21. Controls on the Export of Cultural Objects and Human Rights Kevin Chamberlain and Ana Vrdoljak 22. Foreign Objects and Nationalism Robert K. Paterson and Marc-Andre Renold 23. A Legal Pluralist Approach to International Trade in Cultural Objects Francesca Fiorentini
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.028 |
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".