Bibliographic record
Abstract
The growth of shadow banking in recent decades has changed the concept of banking. It has meant less deposit-taking and lending and more market-oriented banking activities, including in particular a growing trade in securitized products. However, shadow banking is opaque; a problem that was underlined in the recent financial crisis. Does the experience of the financial crisis and its links to the riskiness of banking mean bank re-regulation is necessary? In the Canadian context at least, better reporting of bank risk seems to be a more appropriate way than re-regulation to prevent financial turmoil from arising in this area. Market-oriented operations should be more exposed to daylight, to enable a better evaluation of true bank risk, and regulatory agencies should require detailed reports on activities generating noninterest income. Better indicators of leverage need also to be developed, owing to leverage’s role as the principal channel of bank risk-taking. The advent of shadow banking has fundamentally altered the nature of banking. Where once banks were mainly in the traditional business of taking deposits and making loans, they have come to rely on marketoriented and off-balance-sheet activities to generate a major share of their income. The problem: these activities are utterly opaque, as underlined by their role in the sub-prime financial crisis. The question: what to do about it? Is re-regulation the answer or is there a better way to avoid a repeat of the financial turmoil that originated in this shadowy area?
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.379 | 0.184 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".