Utah County Housing Trends from 2000-2016: A Quantitative Research Analysis
Bibliographic record
Abstract
We examine the Utah County housing market using a sample of over 70,000 single-family residential transactions from 2000 through 2016. To measure the strength of the Utah County residential market, we examine selling price, transaction volume, and number of days the house is on the market. We compare housing prices using two models: a naïve model that calculates the average transaction price over a period, and a hedonic pricing model that gives a detailed, holistic view of how homes are priced. The latter incorporates characteristics of homes not priced in the naïve model. Characteristics include total square feet above and below ground, age of house in years, garage space, total lot area, and other priced factors. When using a hedonic pricing model, we find evidence that home values have experienced a 2.5% annual appreciation from 2000 through 2016. Our study shows that single-family dwellings have increased in line with historical rates over our sample period and not at a real estate bubble pace.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".