A Story of Whales and People: the Portuguese Whaling Monopoly in Brazil (17th and 18th Centuries)
Bibliographic record
Abstract
In this work, the history of the whaling operation in Brazil during the 17th and 18th centuries is recovered. The activity was a monopoly of the Iberian (until 1640) and Portuguese crown, from 1614 to 1801, with economic, political, and ecological significance and impact both for the human and non-human protagonists.The abundance of whales and the valorisation of their products worked as drivers - environmental and economic - for the implementation and development of whaling in Bahia, Rio de Janeiro, São Paulo and Santa Catarina. In its duration, this coastal operation followed the ‘Basque-style’ style with the establishment of fixed whaling stations on land and capturing animals very close to shore. For a short period, sperm whales were captured offshore, using techniques characteristic of the ‘American-Style Shore’. The capture focused on coastal baleen whales, from which oil was produced and baleen plates extracted. Contrary to what was previously assumed, these two products were sent to Lisbon in very significant quantities and periodicity, which allows us a better understanding of their importance in the context of the Portuguese colonisation of the Americas and in a framework of ‘wet globalisation’.This marine extraction not only accompanied the processes of appropriation of the territory but was also a stimulus to promote them. It is argued here that whales played a role in providing a source of wealth for the Portuguese empire and in being an integral element in building relationships between people and the ocean.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".