Signaling effects of recurrent list‐price reductions on the likelihood of house sales
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.
Bibliographic record
Abstract
Abstract Recurrent list‐price reductions for a house may signal the impatience of sellers to conclude a sell transaction more quickly, leading to more visits and a higher likelihood of being sold (positive signal). Recurrent list‐price reductions may also provide a market signal that the listing is problematic and thus harder to sell without a list‐price reduction, leading to a lower likelihood of being sold (negative signal). Unlike standard survival analysis, we investigate which signal prevails using a joint frailty model that accounts for the interdependence among recurrent list‐price reductions and the association between the recurrent reductions and the sold event. Our novel data set contains the time‐dated recurrent list‐price reductions for each house listed on the market. The results from the joint frailty model show time‐varying negative impacts of list‐price reductions on the likelihood of a house sale, supporting the dominance of the negative signaling effects of recurrent list‐price reductions. Although listings with frequent list‐price reductions are less likely to be sold, sold houses sell at a higher ratio of sold price to last list price, which incorporates current market conditions and fairer pricing, holding constant the initial list price and the aggregate list‐price reduction from the initial list price.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it