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Record W1985780231 · doi:10.3141/2017-01

Sustainability in Transport

2007· article· en· W1985780231 on OpenAlexaff
T May, Mary Crass

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsSustainabilitySustainable transportTransport policyPublic transportTransportation planningBusinessPolitical scienceTransport engineeringEnvironmental planningEngineering

Abstract

fetched live from OpenAlex

This paper draws on a review prepared for the meeting of the European Conference of Ministers of Transport in May 2006. Four separate studies were considered: reducing CO 2 emissions from transport, accessibility for those with reduced mobility, implementation of sustainable urban travel policies, and road safety. The purpose of this paper is to draw together the common strands related to sustainable transport and to make recommendations for ministers and their advisers. In doing so, it concentrates on the barriers to achieving sustainability and the ways in which they might be overcome. The paper starts by considering definitions of sustainability and the underlying objectives that governments might pursue. It then considers the varying contexts within which these objectives might be pursued. It reviews the policy instruments that might be employed in achieving these objectives and reviews the barriers to their introduction. Finally, it offers a series of recommendations to governments on ways of overcoming those barriers. The issues raised are of concern to international policy makers. To focus discussion, the questions for ministers in the original version have been recast as issues that policy makers may wish to consider in their own contexts.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.088
GPT teacher head0.450
Teacher spread0.362 · 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 teacher head, not a consensus.

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

Citations54
Published2007
Admission routes1
Has abstractyes

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