Some States Stepping In: Politics and Discourse in Foreclosure Prevention Legislation Outcomes During the Financial Crisis
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
At the core of the 2008 global financial crisis was a foreclosure crisis in the United States. The federal government focused on responding to the concurrent banking crisis, leaving foreclosure prevention to the states. Despite a nationwide crisis, only some states advanced foreclosure prevention policies. Political theory scholars argue that political ideology and economic interests are the primary drivers of policy outcomes, while discourse scholars argue that themes in the public discourse shape policymaking. In this article, I integrate these literatures to develop and test an account of foreclosure prevention policymaking. To measure discourse, I scrape the text of over 20,000 state-level media publications and inductively code them using Structural Topic Modeling. Using event history analysis, I examine the relationship between discourse themes, political factors, and the timing of foreclosure prevention policymaking by state legislatures. I find that states where a “markets” theme was more prevalent in the foreclosure discourse were less likely to advance foreclosure prevention policies, whereas states with discourse focused on “intervention” were more likely to do so. Results also corroborate previous scholarship showing that political ideology and special interest group activity impacted these policy outcomes.
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 | 0.001 | 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