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Record W1557708027

Urban Transportation Indicators - Third Survey

2005· article· en· W1557708027 on OpenAlexaboutno aff
Brian Hollingworth, N A Irwin, Avinash Mishra, Rae Marie Gilbert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaCensusGeographyTransport engineeringSurvey data collectionUrban areaSurvey methodologyUrban planningRegional scienceEngineeringPopulationCivil engineeringEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

In 1993, the Urban Transportation Council (UTC) of the Transportation Association of Canada (TAC) proposed a New Vision for Urban Transportation, describing 13 principles which point the way to desirable future transportation systems and related urban land use. A pilot survey that included eight urban areas was carried out in 1995 using 1991 as the study year. This established baselines that would be used to compare with all future surveys. A follow-up survey was done in 1999 using 1996 as the study year and it included fifteen urban areas, which built on the first survey and compared the two study years. This report describes the third survey, which included all 27 Census Metropolitan Areas (although the level of their participation varies) and was carried out in 2003 for the 2001 study year. This report describes the survey process and results, draws conclusions on trends from the resulting database (which includes 1991, 1996 and 2001 data and which is mounted on the TAC website) and discusses progress towards achieving the TAC Vision in light of the survey findings and in comparison to international data. For the French version of this report, see ITRD number F160238. Pour la version francaise du rapport, voir ITRD numero F160238.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.243
Threshold uncertainty score0.483

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.005

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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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

Citations2
Published2005
Admission routes1
Has abstractyes

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Same topicTransportation Planning and OptimizationFrench-language works237,207