Loyal but French: the negotiation of identity by French-Canadian descendants in the United States
Bibliographic record
Abstract
By focusing on patterns of immigration and acculturation in a small industrial city in the northeastern United States, Mark Paul Richard offers a noteworthy look at the ways in which French-Canadians negotiated their identity in the United States and provides new insights into the ways in which immigrants 'Americanize'.Richard's work challenges prevailing notions of 'assimilation'. As he shows, 'acculturation' better describes the roundabout process by which some ethnic groups join their host society. He argues that, for more than a century, the French-Canadians in Lewiston, Maine, pursued the twin objectives of ethnic preservation and acculturation. These were not separate goals but rather intertwined processes. Underscored with statistics compiled by the author, Loyal but French portrays the French-Canadian history of Lewiston, from the 1880s through the 1990s, in this light.With a wealth of data, the insights of a professional historian, and the sensitivity of a 'local', Richard offers a new conceptualization of ways that immigrants become 'Americans'.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.010 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".