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Record W94062179 · doi:10.5038/2375-0901.5.1.1

Benefits of Proximity to Rail on Housing Markets: Experiences in Santa Clara County

2002· article· en· W94062179 on OpenAlexaboutno aff
Robert Cervero, Michael Duncan

Bibliographic record

VenueJournal of Public Transportation · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueEconomic shortageTransport engineeringBusinessQuarter (Canadian coin)Rail transitLight rail transitMileValue (mathematics)Land valueAgricultural economicsLight railTransit (satellite)FinancePublic transportGeographyEconomicsEngineeringComputer scienceGovernment (linguistics)

Abstract

fetched live from OpenAlex

Santa Clara County, California, home to both light- and commuter-rail services, has turned to transit-oriented development as a means to both reduce traffic congestion and redress severe shortages of affordable housing units. This article examines the degree to which proximity to two forms of rail transit--light rail and commuter rail-- confer benefits to residential properties in terms of sales values. Hedonic price models are estimated that show job proximity over the transit network as well as nearness to rail stops substantially add value to residential parcels. All else being equal, large apartments within a quarter mile of a light-rail station commanded land-value premiums as high as 45 percent. Such market profits not only lure developers to station sites, but also provide a potential source of revenues to local agencies that have set up the kinds of value-recapture programs that allow them to participate inland-appreciation benefits that accrue.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.210
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.060
GPT teacher head0.222
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations130
Published2002
Admission routes1
Has abstractyes

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