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Record W6957942839 · doi:10.6068/dp164f85e1bd451

TREND: Federal Housing Finance Agency. House Price Index: House Price Index - All Transactions | Seasonally Adjusted: Non-Seasonally Adj, 1975/1 - 2018/1. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 057-001-001

2018· other· en· W6957942839 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsUnderwritingIndex (typography)Mortgage insuranceLoan-to-value ratioMortgage underwritingQuarter (Canadian coin)LoanSecuritizationReal estate

Abstract

Federal Housing Finance Agency. House Price Index: House Price Index - All Transactions | Seasonally Adjusted: Non-Seasonally Adj, 1975/1 - 2018/1. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 057-001-001 Dataset: Presents an index (1st quarter 1980=100) of US single-family home prices, by state. All transactions include new purchases and refinancing of conforming, conventional mortgages purchased or securitized by Fannie Mae or Freddie Mac. Only mortgage transactions on single-family properties are included. Conforming refers to a mortgage that both meets the underwriting guidelines of Fannie Mae or Freddie Mac and that does not exceed the conforming loan limit. The House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is published by the Federal Housing Finance Agency (FHFA) using data provided by Fannie Mae and Freddie Mac. The Office of Federal Housing Enterprise Oversight (OFHEO), one of FHFA’s predecessor agencies, began publishing the HPI in the fourth quarter of 1995. The HPI is based on transactions involving conforming, conventional mortgages purchased or securitized by Fannie Mae or Freddie Mac. Only mortgage transactions on single-family properties are included. Conforming refers to a mortgage that both meets the underwriting guidelines of Fannie Mae or Freddie Mac and that does not exceed the conforming loan limit. Conventional mortgages are those that are neither insured nor guaranteed by the FHA, VA, or other federal government entities. Mortgages on properties financed by government-insured loans, such as FHA or VA mortgages, are excluded from the HPI, as are properties with mortgages whose principal amount exceeds the conforming loan limit. Mortgage transactions on condominiums, cooperatives, multi-unit properties, and planned unit developments are also excluded. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975. http://www.fhfa.gov/DataTools/Downloads/Pages/House-Price-Index-Datasets.aspx Category: Housing and Construction, Prices, Consumption, and Cost of Living Subject: Single-Family Housing, Housing Market, Home Prices, Price Indexes Source: Federal Housing Finance Agency The Federal Housing Finance Agency (FHFA) was created on July 30, 2008 by the Housing and Economic Recovery Act of 2008. The agency's primary function is to regulate of the U.S. secondary mortgage market, including oversight of Fannie Mae, Freddie Mac, the 12 Federal Home Loan Banks. http://www.fhfa.gov/

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: other
about Canada: no
confidence: high

US house price index statistical dataset; not about research.

GPT-5.6 (high)OUT
genre: other
about Canada: no
confidence: high

This is a housing-price dataset, not a study of research or its infrastructure.

Grok 4.5OUT
genre: other
about Canada: no
confidence: high

Housing price index statistical dataset documentation; not about research.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.100
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.009
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1000.179

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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2018
Admission routes1
Has abstractyes

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