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Record W1525298235

Economic impact of Light Rail : The results of 15 urban areas in France, Germany, UK and North America

2004· book· en· W1525298235 on OpenAlex
C Hass-Klau, Graham Crampton, Rabia Benjari

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCentAUR (University of Reading) · 2004
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic rentBusinessInvestment (military)Car ownershipAgricultural economicsPedestrianEconomic base analysisLand ValuesEconomic impact analysisGeographyEconomic geographyLand useTransport engineeringPublic transportEconomicsMarket economyEngineeringCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

This report concerns the economic effects of light rail investment in urban transport areas in Europe, Canada and the USA. Effects are divided into direct indicators (values of properties and rent near light rail stations); indirect indicators (pedestrian and car use trends, economic benefits for businesses); and land use indicators (change of retail character). Residential property and rent values were often higher when near a light rail line; office prices were also higher in many cases. New city centre tram stops can increase the number of pedestrians and hence retail turnover: car ownership was seen to be lower per household along tram corridors. It seemed that economic benefits of tram lines accrued to smaller towns as well as larger. Fewer car parking spaces are needed and employers often base new workplaces near good transport links: workers find transport fares less expensive than parking charges. Changes in retail character of a town centre involved a greater number of fashion shops, as rents increase: older industrial areas start to attract leisure and cultural activities.

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 score0.151
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.167
Teacher spread0.161 · 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