Gentrification, Segregation, and Discrimination in the American Urban System
Why this work is in the frame
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Bibliographic record
Abstract
Recent discussions of the ‘geography of gentrification’ highlight the need for comparative analysis of the nature and consequences of inner-city transformation. In this paper, the authors map the effects of housing-market and policy changes in the 1990s, focusing on 23 large cities in the USA. Using evidence from field surveys and a mortgage-lending database, they measure the class selectivity of gentrification and its relation to processes of racial and ethnic discrimination. They find a strong resurgence of capital investment in the urban core, along with magnified class segregation. The boom of the 1990s and policies targeted towards ‘new markets' narrowed certain types of racial and ethnic disparities in urban credit markets, but there is evidence of intensified discrimination and exclusion in gentrified neighborhoods.
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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