La fluidité de l'espace montréalais : étude sur la diffusion de la diversité ethnoculturelle à Montréal entre 2001 et 2006
Bibliographic record
Abstract
Abstract The recent increase in ethno‐cultural diversity has raised numerous questions in countries of immigration. One of them focuses on the processes and mechanisms that lead to the creation of integrated or multiethnic neighbourhoods. To address it, various models were elaborated to explain the phenomenon. We will first recall the main features of these various models. Afterward, we test the hypothesis proposed by Germain and Poirier to explain the evolution of ethno‐cultural diversity in Montreal. This hypothesis supposes that it has evolved in a context where fluidity was central. Our aim is to propose an empirical test of this hypothesis using several methods (i.e., spatial analysis tools, regression model, and structural equation modeling). The results confirm the “fluidity” hypothesis, even if they also stress a stratification process between the various minority groups linked to neighbourhood socio‐demographic characteristics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".