Bibliographic record
Abstract
L'utilisation du b�tail pour produire des substances th�rapeutiques s'est d�velopp�e bien avant que le � pharming � ne vienne r�cemment transformer l'industrie pharmaceutique, gr�ce au g�nie g�n�tique. D�s les ann�es 1870, ont commenc� � appara�tre, en Am�rique du Nord, des � fermes vaccinales � qui devinrent assez vite la principale source du vaccin antivariolique. Au Canada, ces �tablissements perdur�rent longtemps - la derni�re ferme vaccinale fut vendue dans les ann�es 1950 - et ils constituent, en quelque sorte, un exemple de � bio-pharming � de premi�re g�n�ration. Ces fermes repr�sentent un aspect important et peu connu de l'histoire canadienne : le pr�sent article retrace donc les circonstances de leur �mergence, de leur d�veloppement et de leur assimilation au XXe si�cle par des nouveaux laboratoires rattach�s � des universit�s. On constate ainsi que ces fermes apparaissent � la faveur d'une controverse oubli�e jusqu'ici, qu'elles marquent un tournant dont les cons�quences sociales furent majeures - la centralisation et le d�but d'un contr�le plus efficace de la production du vaccin qui permettront d'apaiser les craintes de la population face � la vaccination au Canada - et qu'elles contribuent � ouvrir la voie � l'industrie pharmaceutique canadienne contemporaine. Livestock was used to produce medically useful products long before pharming, a recent offshoot of genetic engineering, transformed the pharmaceutical industry. As early as the 1870s in North America, vaccine farms began to appear that quickly became the primary source of the smallpox vaccine. In Canada, these establishments existed for a long time - the last vaccine farm was sold in the 1950s - and are, to a certain extent, an early example of bio-pharming. Vaccine farms represent a little-known but important aspect of Canadian history. This article traces the circumstances in which vaccine farms emerged, their evolution, and their adoption in the twentieth century by new university laboratories. This article also reminds us of the forgotten controversy amid which these farms existed and argues that they marked a turning point whose social effects were significant - the centralization and the beginning of a more efficient monitoring of vaccine production, one that quelled the fears of a Canadian population faced with the prospect of vaccination. Finally, this article proposes that vaccine farms have paved the way for the current Canadian pharmaceutical industry.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".