MétaCan
Menu
Back to cohort
Record W105801430

Understanding TDM and its Role in the Delivery of Sustainable Urban Transport

2009· article· en· W105801430 on OpenAlexaboutno aff
Colin Black, Eric Schreffler

Bibliographic record

VenueEuropean Transport Conference, 2009Association for European Transport (AET) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsBenchmarkingPublic transportSustainable transportSustainabilityWork (physics)BusinessProcess managementTransport engineeringManagement scienceEngineeringMarketing
DOInot available

Abstract

fetched live from OpenAlex

This paper describes how transport professionals worldwide, particularly in Japan, India, Canada, Australia, USA, New Zealand and in the Far East, have been working together to update understanding of transport demand management (TDM) as a philosophy that underpins the approach to improving the sustainability of transport. A new paradigm in transport planning, which is internationally recognized as TDM, is emerging to embrace mobility management under its umbrella. The paper draws on good practice from across Europe and North America to demonstrate how, through proper understanding of TDM, professionals can be encouraged to work collaboratively towards the sustainable transport policy objective. Furthermore, the paper will explain how TDM unifies the work travel planners, public transport operators, and highway engineers alike to deliver more effective transport solutions. The fascinating results of benchmarking work using the Mobility Enhancement and Trip Reduction Index to aide Comparison (METRIC©) system will be summarized, which is being used internationally to benchmark comparative progress on TDM implementation (including mobility management). The output is report card that can be used by cities to identify opportunities for improvement and what to learn from whom. The paper concludes with the proposition that is needed to form a way to frame the benefits of TDM in terms of a future vision of sustainability that goes beyond the current short term political and operational requirements. The paper will argue that the assumption that ‘mobility management’ interventions help provide a ‘foot-in-the-door’ approach (that will lead individuals up a virtuous ladder of more far-reaching behavioral changes) is fraught with contradictions. Finally, the paper will signpost a growing professional literature that emphasizes the importance of appealing to intrinsic over extrinsic values in order to stimulate longer-lasting behavior change.

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0040.019
Scholarly communication0.0120.019
Open science0.0020.009
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.042
GPT teacher head0.248
Teacher spread0.206 · 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 designQualitative
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

Citations1
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Transport Conference, 2009Association for European Transport (AET)Same topicTransportation Planning and OptimizationFrench-language works237,207