Rural Travel Around an Urban Area: Completing the Picture of Travel
Bibliographic record
Abstract
As the country's urban areas have grown, so too have the rural populations surrounding these centres. Recent urban household travel surveys have tended to include this 'hinterland.' Naturally, the analytical and model development processes have focused on the dominant urban activity whose attributes tend to mask those associated with the surrounding rural areas. However, the characteristics of urban and rural travel differ; and although rural travel is much smaller it does represent a potential new market for sustainable transportation initiatives that are focused on the urban centre. Moreover, the rural 'rings' often provide a transition in travel between interurban corridors and the urban centres - hence regional planning also is impacted. Finally, there is interest in maintaining the character of rural communities and environments in their own rights, which again requires distinct transportation (and other) treatments. Recent travel surveys in the Ottawa-Gatineau area - the National Capital Region, or NCR - provide an opportunity to examine more completely the distinct nature of rural travel. This paper analyzes the 2005 region-wide household origin-destination survey, which also included the rural portions of the NCR. It also considers the 2009 external cordon roadside intercept survey, which looked at travel beyond these rural portions. Together, the two surveys provide insight into the 'complete picture' of travel behaviour in and around the NCR, while also accounting for the differences noted above. For the covering abstract of this conference see ITRD record number 201211RT334E.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.022 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".