An Investigation of Transport-Related Social Exclusion of the At-Risk Community (Homeless People) in Toronto, Canada
Bibliographic record
Abstract
The intersections between transportation and social exclusion demonstrate the significance of public transit as a course of mobility. Low income and homeless individuals (identified as the at-risk community in this paper) are at the most extreme end of social exclusion, and in most cases, public transit is their only possible motorized mode of transport. However, this community is rarely considered in any transport policy development and implementation. This paper focuses on transport-related exclusion of the at-risk community in Toronto with emphasis on the issues related to public transport service accessibility in the city. The research relies on a sample survey among a group of low income and homeless individuals in Toronto in which the frequency of public transit services is identified as the key factor defining transport-related social exclusion experienced by the at-risk community. The paper also investigates the existence of providers of voluntary and community transport services and current urban transportation policies for a most effective examination of this issue. The results of the investigation suggest the need for policy changes for improved at-risk community inclusion in transportation planning processes, increased transit accessibility for low income neighbourhoods, discounted transit fares for particular groups in the community and increased policy integration between the different levels of government.
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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 | 0.010 | 0.002 |
| 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".