A joint analysis of accessibility and household trip frequencies by travel mode
Bibliographic record
Abstract
This paper examines the endogenous relationship between residential level of accessibility and household trip frequencies to tease out the direct and indirect effects of observed behavioural differences. We estimate a multivariate ordered probit model system, which allows dependence in both observed and unobserved factors, using data from the 2016 Transportation Tomorrow Survey (TTS), a household travel survey in the Greater Golden Horseshoe Area (GGH) in Toronto. The modelling framework is used to analyse the influence of exogenous variables on eight outcome variables of accessibility levels and trip frequencies by four modes (auto, transit, bicycle and walk), and to explore the nature of the relationships between them. The results confirm our hypothesis that not only does a strong correlation exist between the residential level of accessibility and household trip frequency, but there are also direct effects to be observed. The complementarity effect between auto accessibility and transit trips, and the substitution effect observed between transit accessibility and auto trips highlight the residential neighbourhood dissonance of transit riders. It shows that locations with better transit service are not necessarily locations where people who make more transit trips reside. Essentially, both jointness (due to error correlations) as well as directional effects observed between accessibility and trip frequencies of multiple modes offer strong support for the notion that accessibility and trip frequency by mode constitute a bundled choice and need to be considered as such.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".