Homelessness vis-à-vis Transportation-Induced Social Exclusion: An Econometric Investigation of Travel Behavior of Homeless Individuals in Toronto, Canada
Bibliographic record
Abstract
The intersection of homelessness and transportation is an overlooked component of transport-related exclusion research, yet mobility is recognized as playing a significant role in anyone’s well-being. The lack of research in this field is concurrent with the lack of understanding of homeless individuals’ mobility needs and travel behavior. As a result, there is little that can guide the policy-making process for the travel needs of homeless individuals. In 2015, as a response to this research gap, an interview was designed and then conducted with 159 homeless individuals across eight shelters and drop-in agencies in the city of Toronto, Canada. The interview included stated adaptation experiments to reveal how transportation affected or hindered homeless individuals’ activity participation processes. Decision choice models were estimated with econometric modeling methods, which indicated the influence of variables such as age, income, and duration of homelessness on the decision to reject or accept employment opportunities. The results also showed that a person’s accustomed mode choice and daily number of trips had an effect on the decision to travel for social activity purposes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".