Abattoirs-Usines, the Modernizing Project for the French Meat Trade, and World War I
Bibliographic record
Abstract
In the early twentieth century, French academic veterinarians launched a meat trade reform movement. Their primary objective was the construction of a network of regional industrial abattoirs equipped with refrigeration. These modern, efficient abattoirs-usines would produce and distribute chilled dead meat, rather than livestock, to centers of consumption, particularly Paris. This system was hygienic and economical and intended to replace the insanitary artisanal meat trade centered on the La Villette cattle market and abattoir in Paris. The first abattoirs-usines opened during World War I, but within 10 years the experiment had begun to encounter serious difficulties. For decades afterward, the experiment survived in the collective memory as a complete fiasco, even though some abattoirs-usines in fact persisted by altering their business models. This article examines the roadblocks of the interwar era and the effects of both the problems and their perception on the post-1945 meat trade.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".