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Record W2023134308 · doi:10.1177/0270467604263564

Traffic Calming: A Social Issue

2004· article· en· W2023134308 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

VenueBulletin of Science Technology & Society · 2004
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTraffic calmingMindsetTransport engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Substantial urban growth fueled by a strong economy often results in heavy traffic thus making streets less hospitable. Traffic calming is one response to the pervasiveness of the automobile. The issues concern built environments and involve multiple actors reflecting different interests. The issues are rarely technical and involve combinations of behavior, social structure, and differential resources. Traffic calming takes many forms by attempting to serve many purposes. It is complex and confusing and is used by different people with different agendas. Traffic calming is not about applying techniques. It is a mindset. We must change both our perceptions and our behaviors. Instead of focusing on end-of-pipe solutions and on things, we must shift attention to the processes that generate things. Trying to accommodate more and more traffic is not the answer. Transportation is a means, not an end. What we are looking at is more people calming than traffic calming.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.003
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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