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Record W2135381177 · doi:10.14714/cp81.1243

Rethinking the Urban Bike Map for the 21st Century

2015· article· en· W2135381177 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

VenueCartographic Perspectives · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdeal (ethics)Order (exchange)CyclingComputer sciencePsychologyPublic relationsAdvertisingSociologyPolitical scienceBusinessHistoryLaw

Abstract

fetched live from OpenAlex

“Bike maps,” commonly produced by city governments to encourage bicycling, tend to rely heavily on subjective recommendations aimed at an ideal “typical cyclist.” Such a typical cyclist is increasingly illusory as people take up cycling for ever more diverse and practical purposes. In order to make bike maps useful for a general audience, we need to rethink some of the basic assumptions these maps have been making. The question should be: what do all cyclists want to know, and how can this information be quantified and depicted such that cyclists can use it to make informed decisions? With this question foremost in mind, we explain the development of a bike map for Cincinnati, Ohio that (almost) completely avoids unquantifiable judgments and, we hope, lights the way for future development of the bike map genre.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.306
Teacher spread0.260 · 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