Did migration alter the path of the demographic transition for French Canadians in the United States?
Bibliographic record
Abstract
Large numbers of Canadians, of both English and French descent, migrated to the United States between 1850 and 1930. In Canada, French-Canadian fertility and child mortality rates were about 50% higher than English Canadian rates. Although the English-Canadian and U.S. white population of native-born parentage experienced rapid fertility declines beginning in the mid to late nineteenth century, there is no sign of significant fertility decline among French Canadians before the twentieth century. We use the number of women's children ever born and the number of surviving children in the IPUMS 1910 full-count census dataset to examine whether migration to the United States altered the timing of the demographic transition for French Canadians. We conduct multivariate analyses to examine correlates of child mortality and fertility (including separate analyses of birth spacing and stopping behaviors), focusing on variables related to the migratory experience. The results indicate that while large differentials in child mortality and fertility persisted between the French- and English-Canadian populations living in the United States, the mortality and fertility of second-generation French Canadians converged significantly toward English-Canadian levels. Other characteristics associated with greater integration into American society yield similar results, with women in exogamous unions, who could speak English, and who resided in enumeration districts with lower proportions of French Canadians experiencing significantly lower fertility and child mortality rates. As expected, the demographic regime of English-Canadian women was similar to US-born women of US-born parentage.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".