Bibliographic record
Abstract
In most countries of the world, car use is increasing, leading to a range of problems. In Great Britain, a quarter of all car trips are less than 3.2 km (2 miles) long and more than half are less than 8 km (5 miles). There is scope to transfer many of these trips to the less harmful alternatives. This paper presents some of the findings from a project entitled Potential for mode transfer of short trips, which was designed to address these issues. The project has been carried out for the UK Department of the Environment, Transport and the Regions (DETR) by the Center for Transport Studies at University College London (UCL) with the survey work sub-contracted to Steer Davies Gleave (SDG). The overall objective of the work was to contribute to Government policy in encouraging the use of the environmentally-benign travel modes in order to reduce the amount of travel by private car. The focus was on the encouragement of the use of walking, cycling and public transport (buses in particular). The focus of this work is `short trips'. In this work these are taken to be those of less than 8 kilometers (5 miles). It should also be noted that this work concentrates on the alternatives to the car that car users perceive and what would make them choose them, rather than on the policies that might make them give up their cars, for example, road pricing. It should be recognized that the actions identified in these surveys are unlikely, on their own, to reduce car use significantly, and that policies that increase the cost of using the car or restrict its use in some other way, would be necessary. The work in this paper will concentrate on car drivers, but car passengers were considered explicitly in the study. In the next section the methodology adopted in the study is described. The analysis begins with consideration of the reasons drivers give for using their cars for short trips. This is followed by discussion of what people say would make them reduce their car use, the alternatives they say that they would consider and the instruments that would encourage them to switch to the alternatives.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".