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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 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.

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

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.060
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