Bibliographic record
Abstract
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.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.018 |
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".