Le laboratoire domestique de la machine humaine: la nutrition, la modernité et l'État québécois, 1860-1945
Bibliographic record
Abstract
This thesis explores the history of nutrition in Francophone Quebec, between the second half of the XIXth century and 1945. It follows the nutritional discourses of doctors, governmental agencies, home economics experts and food corporations. Through the examination of diet and food advice, the thesis identifies values and prescriptive ideals in order to relate them to dominant ideologies and explain their impact on municipal, provincial and federal policies. This dissertation will describe how food habits have been modernized by industrialization and urbanization, and how French-Canadian experts reacted to those transformations in their argumentative and normative food discourses. Nutritional advice promoted a feminine and family ideal that suited French-Canadian nationalism, ruralism and Catholicism, while encouraging women to modernize their cooking as a mean to fulfil their maternal role. But nutrition filled other political goals. As it was taught in schools, promoted to homemakers and broadcasted through public health campaigns and wartime rationing propaganda, nutrition also contributed in the social construction of the ideal citizenship in the liberal order. By describing diet improvements as the result of a maternal, natural, individual and rational work, experts minimized the impact of poverty on food habits and health, therefore justifying non-interventionism. In the 1920s and 1930s, some social scientists and Anglophones nutritionists contested these conceptions and called for programs to aid the redistribution of wealth. Even if those debates contributed in the creation of the welfare state, until 1945, most of the food advice remained socially conservative and supported dominant ideologies and political status quo.
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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 | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".