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Record W2821393491 · doi:10.3390/jrfm11030039

Hedonic Price Function for Residential Area Focusing on the Reasons for Residential Preferences in Japanese Metropolitan Areas

2018· article· en· W2821393491 on OpenAlexvenueno aff
Mitsuru Sasaki, Kayoko Yamamoto

Bibliographic record

VenueJournal of risk and financial management · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaInterpretabilityVulnerability (computing)Hedonic indexFunction (biology)Variable (mathematics)VariablesGeographyExplanatory powerExplanatory modelEconometricsEconomicsPrice indexStatisticsComputer scienceMathematics

Abstract

fetched live from OpenAlex

This study aims to offer a new estimate of the hedonic price function of residential areas in Japanese metropolitan areas, focusing on the reasons for residential preferences. More specifically, it introduces two new explanatory variables—‘regional vulnerability’ and ‘accessibility to destination stations’—and determines their usefulness. Based on the evaluation done in this study, the hedonic price function mentioned above showed 60% interpretability (as compared to 52% interpretability by hedonic price function using only conventional explanatory variables.) In addition, the significance level of both the explanatory variables was low, and the land price changed by 9% as the regional vulnerability changed by 1 grade. Furthermore, residents placed great emphasis on both variables. This made it evident that the introduction of the two explanatory variables that reflect the reasons for residential preferences specific to Japanese metropolitan areas was reasonable.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.026
GPT teacher head0.227
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations14
Published2018
Admission routes1
Has abstractyes

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