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
In cities throughout the United States, blacks tend to live in significantly poorer and lower-amenity neighborhoods than whites. An obvious first-order explanation for this is that an individual''s race is strongly correlated with socioeconomic status (SES), and poorer households can only afford lower quality neighborhoods. This paper conjectures that another explanation may be as important. The limited supply of high-SES black neighborhoods in most U.S. metropolitan areas means that neighborhood race and neighborhood quality are explicitly bundled together. In the presence of any form of segregating preferences, this bundling raises the implicit price of neighborhood amenities for blacks relative to whites, prompting our conjecture that racial differences in the consumption of neighborhood amenities are significantly exacerbated by sorting on the basis of race, given the small numbers of blacks and especially high-SES blacks in many cities. To provide evidence on this conjecture, we estimate an equilibrium sorting model with detailed restricted Census microdata and use it to carry out informative counterfactual simulations. Results from these indicate that racial sorting explains a substantial portion of the gap between whites and blacks in the consumption of a wide range of neighborhood amenities in fact, as much as underlying socioeconomic differences across race. We also show that the adverse effects of racial sorting for blacks are fundamentally related to the small proportion of blacks in the U.S. metropolitan population. These results emphasize the significant role of racial sorting in the inter-generational persistence of racial differences in education, income, and wealth.
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 | 0.015 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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