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Record W7134492998

Bicycle Diversion Evaluation Project

2019· report· en· W7134492998 on OpenAlexaboutno aff
Matthew Callow

Bibliographic record

VenuecIRcle (University of British Columbia) · 2019
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSignagePedestrianPoison controlHuman factors and ergonomicsOrder (exchange)Occupational safety and health
DOInot available

Abstract

fetched live from OpenAlex

The primary purpose of the Bicycle Diversion Evaluation Project (“The BDE Project”) is to determine whether or not wayfinding signage specifically targeted at cyclists, is effective at changing the behaviour of cyclists by encouraging cyclists to use designated bicycle routes. The goal of the wayfinding signs is to encourage cyclists to use routes that are less busy in order to reduce the number of pedestrian-cyclist conflicts on the UBC Vancouver campus. The BDE Project fills a gap in the literature as it is unique. The case studies that were examined in the literature review broadly suggests that signage is effective in changing the behaviour of pedestrians, cyclists or drivers. Despite not clearly being able to identify that bike wayfinding can alter the route choice behaviour of cyclists, the case studies suggest that wayfinding signs will be successful in altering cyclist route choice behaviour. As there is no case study that directly answers the research question being posed in the BDE Project, the BDE Project is an important study that fills a gap in the academic literature on the effectiveness of bike wayfinding signage at changing the behaviour of cyclists. Results from the BDE Project show that the percent change in cyclists choosing to travel away from the Pedestrian Priority Zone in the before-implementation and after-implementation counting period is not significantly different. As a result, the BDE Project cannot confidently conclude that the specific bike wayfinding signs that have been implemented on the UBC Vancouver campus have an effect at altering the route choice behaviour of cyclists. Despite this finding, it is important to understand that there are a number of limitations that likely contributed to this result. One major limitation is the lack of time between the implementation of the wayfinding signs and the beginning of the post-implementation counting. Another limitation of the wayfinding signs is that they are not placed at consistent locations in intersections and have small font size making them hard to read. Further studies looking at the design of bike wayfinding signs are recommended and need to be done before it can be concluded that all bike wayfinding signs are ineffective at altering the route choice behaviour of cyclists. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”

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)0.020
metaresearch head score (Gemma)0.025
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 score0.040
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0400.007

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 head0.041
GPT teacher head0.252
Teacher spread0.211 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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