Bibliographic record
Abstract
Purpose The global economy has entered what appears to be a very serious financial crisis for reasons other than force majeure . While the current focus has to be on preventing a repeat of the Great Depression, efforts must also be made to understand why the crisis came about in the first place. The objective of this paper is to demonstrate that the regulators should have known what the risks were and that these risks were large and systemic, and should have concluded that actions were required to prevent a serious global crisis. Design/methodology/approach The article analyzes the developments in the US mortgage market to assess whether the chances of a crisis in the period before the crisis could have been assessed to be too remote to warrant concern. Findings The evidence seems quite clear that, given the assessments of potential consequences of previous episodes in which concerted actions had to be taken to prevent the collapse of the global financial system, the regulators of the US economy should have taken steps long before the onslaught of chains of collapse of financial institutions that began in the summer of 2007. Originality/value It is hoped that analysis such as this will lead to improvement of regulations of financial markets, reducing chances of future crises of such proportions.
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 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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".