Bibliographic record
Abstract
Research and policy on the geography of assisted housing is dominated by a powerful conventional wisdom: Project-based subsidies are presumptively bad because they anchor assisted households in poor, racially segregated neighborhoods, while vouchers are inherently good because they promote deconcentration and integration through tenant choice. Unfortunately, this consensus is based on geographical assumptions that have been subverted by the dramatic restructuring of cities with tight housing markets over the last generation. In this study, we use the case of New York City to analyze these spatial contradictions. Project-based subsidized housing is disappearing from yesterday's poor neighborhoods that have been remade by gentrification at the urban core, while recipients of Housing Choice Vouchers are concentrated in today's poor neighborhoods of color farther from the city center. If the policy goal is to break the link between housing assistance and the stereotypes of “projects” in the worst neighborhoods, then in the case of tight, expensive urban housing markets, voucher-driven deconcentration will be less successful than the preservation of the existing project-based housing stock.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.220 | 0.076 |
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".