New Brunswick’s Acadia and Francophone Immigrants: A Model of Economic Integration in the Margins
Bibliographic record
Abstract
In the early 2000s, New Brunswick’s Acadia, a Canadian Francophone minority community, became a host community for French-speaking immigrants through activism and the law. The discourse of some of its elites and community organisations is very positive about immigration. However, faced with a multi-dimensional institutional incompleteness in the area of immigration, Acadia erects borders in core sectors of its labour market, namely French-language education and health services. Francophone immigrants are thus pushed to the margins of its labour market, and more precisely to circumstantial and structural employment niches. They realise that they have been selected to take part in French-speaking life and to strengthen the vitality of their host community, but they cannot be part of the French-speaking society as a result of identity issues leading to discriminatory social relationships that prevent them from being fully included in their new host community. A segmented and juxtaposed local Francophonie is thus beginning to emerge due to the lack of integration of immigrants in the Francophone labour market.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.018 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".