Bibliographic record
Abstract
This article studies the effect of immigrant status on mortgage delinquency. Due to their different social and economic background, immigrant households may not integrate well into the host society, and therefore are more likely to be delinquent on mortgages than otherwise identical native‐born households. We test this hypothesis by comparing the mortgage delinquency rate between immigrant and native‐born households in the 2009 PSID (Panel Study of Income Dynamics) data, in which all the immigrant households have been in the United States for more than 10 years. We find that, after controlling for observables, those relatively recent immigrants who have been in the United States for 10 to 20 years have a higher mortgage delinquency rate than native‐born, while immigrants who have resided in the United States for more than 20 years are no different from native‐borns. In addition, there is no evidence that the second generation of immigrants is more likely to be delinquent than the third‐or‐higher generations. Our results are robust to potential sample‐selection bias and functional misspecifications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".