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Record W2256622941 · doi:10.53383/100204

International Real Estate Review

2015· article· en· W2256622941 on OpenAlexaboutno aff
James E. Larsen

Bibliographic record

VenueInternational Real Estate Review · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsSuperstitionReal estateSample (material)EconomicsEstateFinancial economicsBusinessActuarial scienceGeographyFinance

Abstract

fetched live from OpenAlex

A previous study led its authors to conclude that superstition impacts price formation for single-family dwellings in the Vancouver area. Houses there with an address that ends in the "unlucky¨ number 13 are found to sell at a discount compared to otherwise similar houses. The primary objective of this study is to determine whether the previous results apply in another North American housing market. Hedonic regression is applied to single-family house transactions that occurred in Montgomery County, Ohio, to determine if houses with an address of 13 sold for different prices than houses that comprise the remainder of the sample. The same test is then conducted for houses with an address other than 13. No mispricing associated with the number 13 is discovered, but seven other addresses are found to be significantly related to price. As all but one of the significant house numbers identified in this study are not reputed to be particularly lucky or unlucky, we conclude that the price effects discovered are attributable to coincidence. The results of this first study to investigate the possibility of mispricing due to superstition about the number 13 in a residential property market in the United States are consistent with rational market behavior.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.076
GPT teacher head0.305
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2015
Admission routes1
Has abstractyes

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