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Record W2756910502 · doi:10.1177/0042098017724119

Transit-oriented economic development: The impact of light rail on new business starts in the Phoenix, AZ Region, USA

2017· article· en· W2756910502 on OpenAlexaboutno aff
Kevin Credit

Bibliographic record

VenueUrban Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsPhoenixLight railLight rail transitMileBusinessQuarter (Canadian coin)Control (management)EconomyEngineeringTransport engineeringGeographyEconomicsManagementMetropolitan areaPublic transport

Abstract

fetched live from OpenAlex

This article examines the impact of Phoenix’s light rail system, which opened in 2008, on new firm formation in specific industries. Individual business data from 1990–2014 are used in a quasi-experimental adjusted-interrupted time series (AITS) regression to compare the impact of the transit system’s construction on new business starts in ‘treatment’ and ‘control’ areas before and after the opening of the line. Findings show that the transit adjacency is worth an 88% increase in knowledge sector new starts, a 40% increase in service sector new starts and a 28% increase in retail new starts at the time the system opened, when compared with automobile-accessible control areas. However, the light rail also appears to suffer from a ‘novelty factor’– after the initial increase in new establishment activity in adjacent block groups, the effect diminishes at the rate of 8%, 6% and 7% per year, respectively. The results also provide insight into the spatial extent of light rail impacts to new business formation, with areas 1 mile from stations observing 21% fewer retail new business starts and 12% fewer knowledge sector new starts than areas within a quarter of a mile of stations.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.068
GPT teacher head0.343
Teacher spread0.275 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations73
Published2017
Admission routes1
Has abstractyes

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