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Vancouver and the Walker: The Evolution of the Walkable City

2017· book-chapter· en· W2684912452 on OpenAlexaboutno aff
Sandy James

Bibliographic record

VenueTransport and sustainability · 2017
Typebook-chapter
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsWalkabilityNeighbourhood (mathematics)PedestrianEnvironmental planningGeographyPolitical scienceTransport engineeringBuilt environmentEconomic growthCivil engineeringEngineering

Abstract

fetched live from OpenAlex

As a relatively new city by North American standards, Vancouver experienced tremendous growth in the early 20th century. Constrained by its location on a peninsula and surrounded by water, early planning and engineering decisions supportive of citizen accessibility also encouraged and reinforced walkability through strong streetcar networks, walkable neighbourhood commercial areas and the availability of single family housing. Citizen engagement in emerging walkability projects was predicated by the successful stopping of a freeway through the heart of Vancouver. As Vancouver’s planning and engineering policy developed, citizens synergistically worked with the City on several emerging projects that reinforced connection and walkability across the city. Often incepted as demonstration projects, many of these initiatives have been adopted as city policy and have applicability in other jurisdictions.The walkability neighbourhood demonstration projects described can be replicated in other municipalities to create positive impacts on walkability and city life. The effectiveness of these approaches in walkability are echoed in the innovative Olympic Village neighbourhood which housed the athletes at the 2010 Olympic winter games. Many of the concepts and best practices developed in walkable community projects have been melded in creating a successful walking environment garnering world attention. By enhancing walkability in neighbourhood projects, communities strengthened their area’s sustainability and social networks. The synergistic work between the municipality and the community is vital to the success and effectiveness of demonstration projects that can be adopted later as citywide policy.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.584
Threshold uncertainty score0.827

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.004
Scholarly communication0.0090.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.002

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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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