The determinants of state foreclosure rates: investigating the case of Indiana
Bibliographic record
Abstract
Foreclosure rates are defined as mortgages in the foreclosure process as a percentage of all mortgages. These rates vary fairly dramatically across states. While the average foreclosure rate in the 50 states and the District of Columbia in the second quarter of 2007 was 1.25 percent, these rates ranged from a high of 3.60 percent in Ohio to a low of 0.44 percent in Wyoming. One state that has exhibited high foreclosure rates over the past decade is Indiana. Indiana ranked second highest after Ohio in the second quarter of 2007 with a foreclosure rate of 3.01 percent. The goal of this article is to look at the determinants of state foreclosure rates with particular attention to the set of factors referred to in discussions of Indiana’s high rates. Three primary factors have been responsible for Indiana’s high foreclosure rates: the poor performance of the housing market and economy, the high levels of subprime and FHA borrowing in the state, and the relatively long duration of Indiana foreclosures. However, even after taking these factors into account, Indiana’s foreclosure rates are higher than would be anticipated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".