Evaluating the Potential of Transportation-Related Social Exclusion of Elderly People: An Application of a Joint Mode Choice and Travel Distance Demand Model in the National Capital Region (NCR) of Canada
Bibliographic record
Abstract
This paper uses a utility-theoretic econometric model to investigate the joint mode choice and travel distance of elderly people (age 65+). The main objective is to investigate the possibility and extent of transportation-related social exclusion of elderly people. Empirical models are estimated by using a household travel survey conducted in the National Capital Region (NCR) of Canada. Modal accessibility is considered as a determinant of travel distance. The spatial expansions method is used to capture spatial dispersion and disparity of elderly people for different activity types. Multi-variable interactions are used to capture systematic variations of total distance travel demand across age groups for different activity types. Empirical model reveals that elderly people living in the NCR are prone to transportation-related social exclusion. It is evident that the effects of poor accessibility and unfavourable land use patterns are not the same across the region. The NCR is proven to be a monocentric and central business district (CBD) oriented region. Elderly people living far from the CBD need to travel longer distances that further increase with age. With an increasingly elderly population in the region, the risk of transportation-related social exclusion also increases. Most importantly, transportation-related social exclusion in the NCR is driven more by the region’s urban form and land use patterns than the performance of the regional transportation system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".