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Record W3082094726 · doi:10.1080/19427867.2020.1803542

Rule compliance and desire lines in Barcelona’s cycling network

2020· article· en· W3082094726 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransportation Letters · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsVancouver Community CollegeUniversity of British Columbia
Fundersnot available
KeywordsIntersection (aeronautics)CyclingTransport engineeringComputer scienceEngineeringGeography

Abstract

fetched live from OpenAlex

A major challenge in the development of new cycling infrastructure is the design of intersections that are safe, appropriately used, and inclusive. In this paper we study how cyclists interact with existing street design at intersections in Barcelona. We observed rule compliance (n = 5,063) and desire lines (n = 5,082) at six intersections over 12 weekdays. We find that 78.9% of cyclists comply with intersection rules. Rule incompliance is associated with the gender of the cyclists, the directionality of the bike lanes that intersect, traffic signals, and performing a turn. Our analysis of desire lines through the intersections illustrate that incompliant behavior is driven by a need for uninterrupted travel, and highlight systemic and design features that contribute to incompliance. We suggest ways to improve intersection design and safety: i) prioritize unidirectional bike lanes; ii) optimize traffic lights, and; iii) anticipate cyclists’ desired trajectories when designing new cycling infrastructure.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

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

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 head0.062
GPT teacher head0.304
Teacher spread0.242 · 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