Troubled Asset Relief Program: Status of Efforts to Address Defaults and Foreclosures on Home Mortgages
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "A dramatic increase in mortgage loan defaults and foreclosures is one of the key contributing factors to the current downturn in the U.S. financial markets and economy. In response, Congress passed and the President signed in July the Housing and Economic Recovery Act of 2008 and in October the Emergency Economic Stabilization Act of 2008 (EESA), which established the Office of Financial Stability (OFS) within the Department of the Treasury and authorized the Troubled Asset Relief Program (TARP). Both acts establish new authorities to preserve homeownership. In addition, the administration, independent financial regulators, and others have undertaken a number of recent efforts to preserve homeownership. GAO was asked to update its 2007 report on default and foreclosure trends for home mortgages, and describe the OFS's efforts to preserve homeownership. GAO analyzed quarterly default and foreclosure data from the Mortgage Bankers Association for the period 1979 through the second quarter of 2008 (the most recent quarter for which data were available). GAO also relied on work performed as part of its mandated review of Treasury's implementation of TARP, which included obtaining and reviewing information from Treasury, federal agencies, and other organizations (including selected banks) on home ownership preservation efforts. To access GAO's first oversight report on Treasury's implementation of TARP, see GAO-09-161."
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".