Rise of the Renter Nation: Solutions to the Housing Affordability Crisis
Bibliographic record
Abstract
Private homeownership cannot serve as our only model for decent, stable housing. While the most recent speculative bubble raised the proportion of homeowners nationwide to 70 percent of all households, this gain was an illusion that vanished as the market collapsed. A longer view reveals that for three decades before the bubble began in the mid-1990s, homeownership rates hovered around 64 percent, despite massive federal and market support. Further, the historic average obscures important and severe racial disparities in homeownership rates, which have never exceeded 50 percent for black and Latino populations. Yet, policy and even much of the progressive analysis of the housing crisis seem incapable of acknowledging -- much less acting on -- these realities. The result is a national dialogue about the housing crisis that all but ignores the growing renter class, where the crisis is concentrated, and retains a myopic focus on private ownership. The following report is a reality check. It attempts to redirect the conversation and provide an agenda for genuine housing security for all.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".