The Changing Spatial Distribution of Montreal Seniors at the Neighbourhood Level: A Trajectory Analysis
Bibliographic record
Abstract
Numerous studies in the 1970s and 1980s examined the changing residential geography of seniors in North American metropolises but recent studies are scarce. The goal of this paper is to identify and model neighbourhood ageing trajectories in Montreal over six consecutive census years (1981–2006). To identify these trajectories, we use a statistical method, Latent Class Growth Modelling, applied to location quotients calculated at the census tracts level (neighbourhoods). The 614 neighbourhoods are classified according to eight ageing trajectories. Next, we examine the predictors of these trajectories by introducing two types of variables: variables characterizing residents and the built environment at the beginning of the study period, and variables that consider the evolution of these characteristics over the 25-year time frame. The most important predictors are the proportions in 1981 of persons 45–64-years old, of one-person households and of low-income families, and the variation from 1981 to 2006 in proportions of persons 0–14-years old and of one-person households.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".