Financial Institutions in Distress
Bibliographic record
Abstract
Abstract Political boundaries are often porous to finance, financial intermediation, and financial distress. Yet they are highly impervious to financial regulation. When inhabitants of a country suffering a deficit of purchasing power are able to access funds flowing in from a country with a surfeit of such power, the inhabitants of both countries may benefit. They may also benefit when institutions undertaking such cross-border intermediation experience economies of scale and are able to innovate and to offer funds and services at lower costs. Inevitably, however, at least some such institutions will sometimes suffer distress in one country and may then transmit such distress to other countries in which it operates. The efficacy of any response to such cross-border transmission of distress may turn on the response being given due effect in both (or all) the territories in which the distressed financial institution operates. This situation creates a conundrum for policymakers, legislators, and regulators who wish to enable those subject to their jurisdiction to access the benefits of cross-border financial intermediation, yet cannot make rules and regulations that would have effect outside that jurisdiction. This book explores this conundrum and offers a response. It advocates for the creation of a model law that would address the full range of financial institutions, and that would enable relevant authorities to cooperate with counterparts in advance of the onset of distress and to give appropriate effect in their jurisdiction to measures taken by counterpart authorities in other jurisdictions in which the distressed institution also operates.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".