Commuting on the Canadian Prairies and the Urban/Rural Divide
Bibliographic record
Abstract
Abstract Using 2001 data, we perform a statistical analysis to identify factors that influence commute distance for households on the Canadian Prairies. The lack of regional-based commuting studies in Canada, along with formerly unavailable data on commuting distance by census subdivision (CSD) and our use of geographical information systems (GIS) applications, makes this study unique in its scope. We highlight factors that distinguish between urban and rural commuters. For instance, rural residents appear to be more concerned with access to jobs than reducing commuting distances while the presence of good roads in isolated rural areas is critical for providing access to jobs in neighbouring urban centres. In addition, we find certain similarities in commuting patterns across urban and rural areas, indicative of the tight knit between urban and rural communities in this region. Résumé À l'aide de 2001 données, nousfaisons une analyse statistique pour identifier les facteurs qui influencent la distance des trajets parcourues quotidiennement par les ménages dans les prairies canadiennes. L'étude est unique en son genre en raison de l'absence d'études régionales sur les trajets quotidiens, de l'inexistence, par le passé, auprès du Secteur du Recensement, des données sur les distances parcourues quotidiennement par les populations et de l'utilisation du système de renseignement géographique. Nous mettons en évidence les facteurs qui différencient les navetteurs urbains des navetteurs ruraux. Par exemple les navetteurs ruraux semblent se préoccuper plus de l'accès aux emplois que de la réduction des distances à parcourir. Par ailleurs, l'existence des routes viables dans les zones rurales enclavées est indispensable pour l'accès aux emplois dans les centres urbains environnants. Nous relevons certaines similitudes dans les configurations des distances à parcourir dans les zones urbaines et les zones rurales, similitudes qui illustrent les liens serrés entre les communautés urbaines et rurales dans cette région.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".