Bibliographic record
Abstract
Banking system crises are complex events that in a short span of time can inflict extensive damage to banks themselves and to the external economy. The crisis literature has so far identified a number of distinct effects or channels that can propagate distress contagiously both directly within the banking network itself and indirectly, between the network and the external economy. These contagious effects, and the potential events that trigger these effects, can explain most aspects of past crises, and are thought to be likely to dominate future financial crises. Since the current international financial regulatory regime based on the Basel III Accord does a good job of ensuring that banks are resilient to such contagion effects taken one at a time, systemic risk theorists increasingly understand that future crises are likely to be dominated by the spillovers between distinct contagion channels. The present paper aims to provide a model for systemic risk that is comprehensive enough to include the important contagion channels identified in the literature. In such a model one can hope to understand the dangerous spillover effects that are expected to dominate future crises. To rein in the number and complexity of the modelling assumptions, two requirements are imposed, neither of which is yet well-known or established in the main stream of systemic risk research. The first, called stock-flow consistency, demands that the financial system follows a rigorous set of rules based on accounting principles. The second requirement, called Asset-Liability symmetry, implies that every proposed contagion channel has a dual channel obtained by interchanging assets and liabilities, and that these dual channel pairs have a symmetric mathematical representation.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".