Has mortgage capital found an inner‐city spatial fix?
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 For two generations, urbanists have analyzed how residential mortgage lending reflects and reinforces inner‐city inequality. Yet the basic dichotomies of this literature have been eroded by parallel developments in community organizing, public policy, and restructuring of financial services. Securitization, institutional structure, and increasingly sophisticated market segmentation have altered the relationship between mortgage capital and the inner city, redrawing patterns of exclusionary redlining into more complicated, stratified inclusion into prime and subprime reinvestment flows. In this article, we analyze lending dynamics in neighborhoods at the nexus between gentrified reinvestment and enduring poverty in 23 large U.S. cities. A strong, sustained resurgence of capital investment is woven together with enduring racial‐ethnic exclusion that cannot be blamed on borrower deficiencies. Institutional restructuring and secondary‐market linkages reinforce newer class and racial‐ethnic inequalities through subprime segmentation: Lenders’ willingness to serve black borrowers, for instance, is becoming closely associated with subprime specialization.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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