Subcentres as Destinations: Job Decentralization, Polycentricity, and the Sustainability of Commuting Patterns in Canadian Metropolitan Areas, 1996–2016
Bibliographic record
Abstract
Adopting more sustainable modes of transportation and shorter daily commutes remains a fundamental challenge in the struggle for the sustainable transition of cities. While past studies on the sustainability of commuting behaviours partly focused on the place of residence and how the characteristics of commuters or residential neighbourhoods impact sustainable travel, other studies looked at the place of employment to analyze these dynamics. In this study, we investigate the extent to which the recent phase of the rise of peripheral employment has promoted more sustainable travel behaviour, based on the hypothesis that polycentricity has recently favoured a better job–housing balance and co-location. We develop a general typology of employment centres, using Census microdata at fine spatial scale over the 1996–2016 period to observe commuting modes and distances by subcentre types for six major Canadian cities. Our results show that despite recent developments in planning practices—transit-oriented development, transport infrastructure, and changing travel behaviour, the emergence of peripheral subcentres promoted less sustainable commuting patterns in most Canadian metropolitan areas over the period. However, we find sustainable commuting emerging in subcentres where large public transport infrastructure investments have been made, such as in the case of Vancouver’s Millennium and Canada lines. Our study also shows that central business districts (CBDs) and downtown subcentres are becoming relatively more sustainable over the period, which confirms the positive effect of the back-to-the-city movement and changing behaviour toward active transportation in these locations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".