Shipper Preferences Suggest Strong Mistrust of Rail
Bibliographic record
Abstract
The Quebec City–Windsor corridor is the busiest and most important trade and transportation corridor in Canada. The transportation sector is the second-largest contributor to greenhouse gas emissions in the country. Governments around the world, including Canada's, are considering increasing mode share by rail as a way of reducing transportation emissions. To understand whether freight mode shift is a realistic means of reducing transportation emissions, an analytical model is needed that can predict the effect of government policy on mode split. This paper presents the findings of the first such model developed for the Quebec City–Windsor Corridor. The model itself is a stated preference carrier choice model of shippers in this busy route. The model was developed by using the results of a stated preference survey undertaken in fall 2005. The survey was designed explicitly to evaluate shipper preferences for the carriage of intercity consignments, particularly their preferences for carriers that contract the services of rail companies to carry these shipments via rail. The results of the study (a) show that shippers are mistrustful of using rail to move their consignments and (b) suggest that increasing rail's share of freight transport faces tremendous challenges.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".