Toward an Understanding of the Built Environment Influences on the Carpool Formation and Use Process: A Case Study of Employer-based Users within the Service Sector of Smart Commute’s Carpool Zone
Bibliographic record
Abstract
The recent availability of geo-enabled web-based tools creates new possibilities for facilitating carpool formation. Carpool Zone is a web-based carpool formation service offered by Metrolinx, the transportation planning authority for the Greater Toronto and Hamilton Area (GTHA), Canada. The carpooling literature has yet to uncover how different built environments may facilitate or act as barriers to carpool propensity. This research explores the relationship between the built environment and carpool formation. With respect to the built environment, industrial and business parks (homogeneous land-use mix) are associated with high odds of forming carpools. The results suggest that employer transport policies are also among the more salient factors influencing carpool formation and use. Importantly, the findings indicate that firms interested in promoting carpooling will require contingencies to reduce the uncertainty of ride provision that may hamper long-term carpool adoption by employees.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".