MétaCan
Menu
← Back to cohort
Record W600493996

Host city Olympic transportation plan: survey data analysis and discussion

2010· article· en· W600493996 on OpenAlexaboutno aff
Ching‐Wen Lin, Tarek Sayed

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownDocumentationPlan (archaeology)GeographyGeneral partnershipPeninsulaSustainable transportTraffic calmingHost (biology)Transport engineeringBusinessAdvertisingSustainabilityEngineeringArchaeologyComputer scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

The City of Vancouver, in partnership with TransLink, VANOC, and Transport Canada, appointed the Civil Engineering Department of the University of British Columbia (UBC) to conduct the monitoring of transportation through the Vancouver Downtown peninsula during the 2010 Winter Games. The data comprised of 3 samples of 24hr and partial-day screenline counts of all travel entering or leaving the downtown area by all modes. Additionally, intercept surveys captured the travel behaviour and choices of spectators and participants of Downtown Olympic-related events. In summary, the results of the monitoring study suggest the provision and uptake of transportation during the 2010 Winter Games was successful and a new Olympic record of a 24-hour 61 per cent sustainable mode share into/out of the Downtown core was observed. The Host City Downtown Monitoring Study documents the observed sustainable transportation behaviour during the 2010 Winter Games as a lasting legacy. The study is also an objective documentation that local residents and visitors can adjust to travel in a much more sustainable manner than normal.

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)0.006
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.082
GPT teacher head0.356
Teacher spread0.274 · 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicSport and Mega-Event Impacts→French-language works237,207→