Bibliographic record
Abstract
In the hundred years ending in 1930, an estimated 2.8 million Canadians moved south of the 49th Parallel and settled in the United States. The human and technical resources they brought made Canadian immigrants integral to the growth of New England, the Great Lakes region, and the west coast. Crossing the 49th Parallel is the first book to encompass that entire, continent-wide population shift. It brings Canadian migration to the center of both Canadian and U.S. history. Bruno Ramirez researches the contents of previously unused border records to bring to light the wide variety of local contexts and historical circumstances that led Canadian men, women, and children to cross the border and become key actors in the U.S. economy and society. Ramirez goes beyond these statistical data, consulting qualitative sources and case studies to reveal the motives and aspirations of individuals and family groups. The comparative perspective of Crossing the 49th Parallel allows Ramirez to explain the distinctive roles of French- and Anglo-Canadians in the immigrant movement. By shifting the viewpoint from a continental to a transatlantic one, Ramirez also unveils Canada's important role in international migration; it served as a temporary destination for many Europeans who subsequently remigrated to the United States.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".