Overview of Brazilian Geographical Indications and the Experience of Cachaca Indications of Procedure
Bibliographic record
Abstract
The Geographical Indication (IG) is an Industrial Property asset that relates and distinguishes the geographic origin of a product or service. In Brazil, it can be classified as an Indication of Origin (IP) or Denomination of Origin (DO). This study aims to provide an overview of the deposits of Geographical Indications in Brazil, from the publication of Law nº 9.279, of May 14, 1996, the Industrial Property Law, and the recognition of Indications of Origin and Denomination of Origin by the National Institute of Intellectual Property (INPI) between 1996 and 2022. Given this context, theoretically based on the concepts of territory and territoriality, the highlight of initiatives to register GIs of Cachaça in Brazil is highlighted. The exploratory research was carried out through secondary sources and the method chosen was of a qualitative nature, using the techniques of bibliographic and document review. As a result, it was found that, during the study period, there was an expansion in the number of GI records, concentrated mainly in the Southeast and South regions, but far below the existing potential in Brazil, given the existence of socioeconomic, geographic factors, environmental, ethnocultural, institutional, in addition to the characteristics of agricultural activity. Furthermore, the number of IPs registered with the INPI corresponds to approximately 70% of Brazilian GIs and only 3 of them have cachaça-type sugarcane brandy as a product.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".