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Record W603504559

REDUCING CAR USE FOR SHORT TRIPS {PRIVATE}

2001· article· en· W603504559 on OpenAlexaboutno aff
RL Mackett

Bibliographic record

VenueSelected Proceedings of the 9th World Conference on Transport ResearchWorld Conference on Transport Research Society · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsTRIPS architectureWork (physics)Public transportTransport engineeringQuarter (Canadian coin)Scope (computer science)Government (linguistics)BusinessOrder (exchange)KilometerMode choiceEngineeringGeographyFinanceComputer science
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0340.005

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.

Opus teacher head0.192
GPT teacher head0.386
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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