Geographical Indications Between the <i>Old World</i> and the <i>New World</i>, and the Impact of Migration
Bibliographic record
Abstract
Abstract The article focuses on the use of European geographical names in certain countries of the so-called ‘New World’ (i.e. nations reached in the past by waves of European migration) and the impact of such migration on the debate around the protection of geographical indications (GIs). Specifically, the article analyses four GIs case studies – ‘Prosecco’, ‘Budweiser’, ‘Rioja’ and 'Parmesan' – which highlight the role of migration in this context and how countries of the New World (e.g. US, Canada, Australia, etc.) emphasise this role to argue that several European geographical names of food and wine products are just the generic terms for the products themselves. The ‘migration’ factor however is downplayed by the EU (i.e. the Old World), which stresses that European GIs still have a distinctive function linked to the geographical origin of the underlying product and should be protected in Europe and beyond.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".