CHAPTER 8. THE ECONOMICS OF GOVERNMENT HOUSING ASSISTANCE FOR THE POOR
Bibliographic record
Abstract
Since the 1930s, the federal government has undertaken several major efforts to provide housing assistance to low-income individuals. The government attempts to help low-income individuals reduce housing costs or improve the quality of housing consumed through a variety of programs, most of them administered through the U.S. Department of Housing and Urban Development (HUD). In the past, the majority of federal housing assistance occurred through the construction of public housing while today most federal housing aid occurs through rental assistance programs (U.S. House of Representatives 2004). In constructing publicly owned and managed housing, government attempts to increase the quality of the housing stock available to low-income individuals. Rental assistance programs, on the other hand, try to increase the quality of low-income housing either through building or rehabilitation programs geared toward low-income households or through direct subsidies that allow low-income households to rent better private units than they otherwise would rent. These two types of housing assistance come under a variety of different programs and in various forms, but at the core they comprise two somewhat distinct approaches to providing housing assistance to the poor. In real terms, total outlays for all housing programs administered by HUD have grown over the past quarter century (Table 1). From 1977 to 2002, total spending by HUD on all of its housing programs grew from $7.2 billion to $31.8 billion even after
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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 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".