Migrations canadiennes-françaises au 19<sup>e</sup> siècle : un exemple de jumelage censitaire transnational
Bibliographic record
Abstract
Cet article a pour but d’illustrer l’utilité des méthodes de jumelage automatique pour l’étude des migrations canadiennes-françaises au Canada et aux États-Unis 1 . Il détaille la construction d’un échantillon longitudinal géolocalisé de près de 30 000 hommes catholiques du Québec issu du jumelage des recensements canadiens et américains de 1850-1852 et 1880-1881. Cet échantillon offre la possibilité de répondre à de nombreuses questions tant sur la composition de la diaspora canadienne-française que sur les flux migratoires internes au Québec. Un arrimage entre l’échantillon, qui est composé de migrants et de non-migrants, et les données censitaires agricoles agrégées suggère une association négative entre la prospérité agricole de la communauté d’origine et la propension à migrer.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".