Mapping (In)Formal Francophone Spaces: Exploring Community Cohesion Through a Mobilities Lens
Bibliographic record
Abstract
Immigration is being used as a policy lever to sustain the demography of Canadian Francophone minority communities (FMCs). As FMCs become increasingly diverse, concerns have been raised regarding their capacity to develop and sustain a sense of community cohesion. This study draws on the mobilities paradigm to examine how community members within three different FMCs engaged within and beyond formal and informal Francophone spaces within the cities of Metro Vancouver, Winnipeg and Moncton. Using an occupational mapping method to elicit spatial and dialogic data, we analyze the descriptions of maps from 62 French-speaking participants who were born in, or who immigrated to, Canada in order to obtain diverse perspectives on community cohesion. Our findings are presented according to three themes. The first addresses socio-geographically shaped mobilities within the three FMCs, the second examines participants’ engagement in a range of (in)formal Francophone spaces, and the third explores their convergent and divergent mobilities as shaped by local dynamics. We contribute insights into the relationship between forms of spatial and social mobility that shape experiences of community cohesion within FMCs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".