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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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