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Record W615276689

Moving more with less: integrated transportation demand management at the University of British Columbia

2007· article· en· W615276689 on OpenAlexaboutno aff
Carole Jolly

Bibliographic record

VenueTransport Research Forum · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownGrowth managementGeneral partnershipRegional planningGovernment (linguistics)Transport engineeringPlan (archaeology)BusinessSustainable transportTransportation planningLand-use planningLocal governmentLand useEnvironmental planningUrban planningSustainabilityGeographyPolitical scienceEngineeringPublic administrationFinanceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

The University of British Columbia (UBC) is in a geographically isolated area away from the downtown core of Vancouver. With an average growth rate of 2 per cent per year and an aggressive neighbourhood development plan, this has encouraged UBC to take a proactive approach in developing strategies to pursue sustainable transportation targets aimed at reducing single occupancy vehicle traffic, while increasing transit ridership and other alternative mode choices To this end, in partnership with the Greater Vancouver Regional District, an official community plan was developed in 1997, with the intent to help guide all future campus growth and development in accordance with the Greater Vancouver Regional District (GVRD)s Livable Region Strategic Plan (LRSP). The LRSP is the GVRD's regional growth strategy aimed at maintaining regional livability and protection of environment in the face of anticipated growth. All levels of government use the LRSP as the framework for making regional land use and transportation decisions. (a) For the covering entry of this conference, please see ITRD abstract no. E216058.

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)0.001
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 score0.779
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.000
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.028
GPT teacher head0.304
Teacher spread0.276 · 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
Published2007
Admission routes1
Has abstractyes

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