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Record W2913532086 · doi:10.1111/1540-6229.12275

The Effect of a Subway on House Prices: Evidence from Shanghai

2019· article· en· W2913532086 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

VenueReal Estate Economics · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsContext (archaeology)ChinaCentral business districtCenter (category theory)Demographic economicsLine (geometry)EconomicsHouse priceLabour economicsBusinessGeographyTransport engineeringEngineeringEconometrics

Abstract

fetched live from OpenAlex

Abstract Within the context of a transition economy, this article estimates how improved access to employment centers is capitalized into house price. We conduct an event study for the opening of subway Line 6 in Pudong district, Shanghai, China. The new line significantly reduces the commuting time to major employment centers. Other things being equal, easier commutes to the central business district center result in an average house price appreciation of 3.75%, with the most distant residential zone enjoying the largest appreciation. When taking into account multiple employment centers, we find that the largest source of appreciation is from an improved access to a suburb center with poor initial accessibility and attractive job opportunities. Finally, the total appreciation caused by time savings to major employment centers decreases with neighborhood income level and increases with the distance from Line 6 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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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