Transformation marquante dans la configuration spatio-linguistique de la région de Moncton au Canada / A significant transformation in the linguistic configuration and of the cultural identifies in the Greater Moncton, Canada
Bibliographic record
Abstract
Located in the heart of the Maritimes in Southeast New Brunswick, Moncton has the highest concentration of Acadians in any urban setting in Canada. Over the years, Acadians have increasingly become part of the New Brunswick society. They have greatly contributed to Moncton's development through the creation of genuine Acadian institutions in the educational and financial sectors, which, as a result, have modified the spatio-linguistic configuration and the cultural identity of the place. This new reality has been the object of a series of spatiotemporal analyses using the Geographic Information System (GIS); they show that the dynamics of the Francophone and Anglophone populations in the agglomeration's different sectors lead to the creation of some isolated linguistic groupings. And that unlike the situation in other regions of New Brunswick, the assimilation process of the French-speaking Acadians into the Anglophone majority has slowed down in the Greater Moncton over the course of the last few years. These transformations point out to the crucial role of the Universite de Moncton as an educational, cultural and even political nexus for the Acadians in the Greater Moncton, as well as in the Maritime provinces in general.
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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 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".