Question worth 20 million lives: Why federal housing assistance has not had its Obamacare
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 The equitable character of a policy determines its progressiveness, yet some domestic policies are more equitable than others. The question of how and why this is the case is addressed by studying federal housing and health policies in the United States, a critical case known for its rampant inequalities in both sectors. Although social equity is a fundamental aspect of welfare provision, explaining differences in coverage and government support among policy areas remains a weakness in the literature. This comparative historical analysis shows that both housing assistance and health care suffered from inequities almost as early as their inception. But a progressive reform took shape with the Affordable Care Act (ACA) and extended coverage to 20 million people formerly uninsured. This essay tackles an unsolved puzzle: Why has such grand policy reform never taken place in housing where more than 20 million people are eligible for assistance but do not receive help? We found that it is largely explained by housing assistance distinctiveness with regard to its weak constituency, racial connotation and low public concern. We conclude with the analytical payoffs of studying social equity, both for political scientists and observers of social affairs.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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