Linguistic and Economic Characteristics of Francophone Minorities in Ontario and New Brunswick from 1981 to 2011
Bibliographic record
Abstract
This paper uses the 2011 National Household Survey to analyze the economic position of the Francophone minorities of Ontario and New Brunswick. The results are compared with earlier ones for 1981 and 1991 obtained by Grenier (1997). Demographic and other characteristics that are related to economic success are first considered. Earnings regression models are then estimated to analyze the gross and net earnings gap between Anglophones and Francophones. Finally, the paper considers a new factor, immigration in Ontario, that has become important in recent times. The major results are as follows. First, assimilation to English by Francophones is higher in Ontario than New Brunswick, and the assimilation rate has increased in both provinces since 1991. Second, the gap between Francophones and Anglophones in the characteristics that are related to economic success has decreased. Third, most Francophones no longer have an earnings disadvantage in 2011, and some even earn more than Anglophones. Finally, immigrants who speak other languages at home have a large earnings disadvantage, while it is not the case for those who speak French at home.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".