La dynamique spatiale des marchés locaux de l'emploi au sein du champ métropolitain de Québec, 1981–2001
Bibliographic record
Abstract
Spatial Dynamics of Local Labour Markets in the Québec City Metropolitan Field, 1981–2001 This research analyzes the spatial dynamics (from 1981 to 2001) of local labour markets at an infra‐regional scale, namely the Québec metropolitan field, with particular emphasis on interactions between the metropolitan region and its hinterland. It seeks to better understand the factors underlying this evolution. Centrographic analyses were performed to characterize the evolution of the spatial configuration of local labour markets (displacement of gravity centre, shape change, evolution of dispersion indices and of workforce preferential distribution axes). Between 1981 and 2001, almost all employment poles experienced an increase in the mean‐distance tied to their recruitment area, that being particularly true for peri‐metropolitan poles which employ an increasing part of their workforce inside the metropolitan labour basin, where a more qualified and diversified labour force is available; thus, giving rise to significant reverse commuting. In addition to the influence of distance to metropolitan area, a multiple regression model shows that factors such as manufacturing specialization and employment growth within job centres also play a crucial role in the spatial dynamics of local labour markets in the Québec City metropolitan field.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".