From <i>Mangons</i> to <i>Rewards</i> : Butchery Animals as Revealing the Diversity of Trades in Belgian Cities in the Early Modern Period
Bibliographic record
Abstract
Focusing on the Belgian cities of Namur and Liège in the eighteenth century, this article proposes to open a discussion around legal versus illegal butchery, and the description of how it was regulated: by limiting slaughter to specific locations, specific trades, and specific times, and by the work of the people in charge of inspecting foodstuffs. At the heart of this study is the butchery animal—that is, large animals—and the profession in charge of it: the butchers. Given the importance of meat products in consumption practices, the city’s butchers had a central place: gathered in a guild, they had a privileged status, including a virtual monopoly on the slaughter of butchery animals and the sale of raw meat. However, as the meat economy was developing, master butchers were faced with a multitude of vendors who undermined their position and threatened health standards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".