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Seismic Retrofit Added 17% to the Resale Value of Older California Houses

2022· article· en· W4293157153 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

VenueNatural Hazards Review · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsNetwork for Business Sustainability
Fundersnot available
KeywordsCrippleBracingIncentiveValue (mathematics)Foundation (evidence)OccupancyBusinessHazardEngineeringForensic engineeringEconomicsCivil engineeringMicroeconomicsComputer scienceLawStructural engineeringPolitical science

Abstract

fetched live from OpenAlex

We examined the resale prices of 217 recently sold California single-family dwellings built before 1960 to determine whether buyers value seismic retrofit. Of these, sellers indicated that 29 houses had been seismically retrofitted: 17 pre-1940 houses (when unanchored foundations and unbraced cripple walls were common) and 12 built between 1940 and 1959 (when unbraced cripple walls were common). A stepwise regression analysis indicates that in 2020 California home buyers paid 17% more for retrofitted pre-1940 houses. Buyers may have paid about 1% more for retrofitted 1940–1959 houses, but the correlation is weak. A higher resale price is a powerful incentive for people to invest in foundation bolts and cripple wall bracing. It reinforces findings by other researchers that natural hazard mitigation not only saves (by avoiding future losses), but it also pays (through higher resale value).

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0020.001

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 head0.241
Teacher spread0.221 · 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