Preliminary and Incomplete: 5-11-00 (Do not quote without permission)
Bibliographic record
Abstract
nments differ in notable ways: in economic geography, in regulatory architecture, in patterns of interbank competition, and in governmental organization. Although not experimentally controlled, such differences can be measured and interpreted as treatments applied to "experimental" and "control" groups. By analyzing the effects of putative policy treatments, we hope to assemble a body of tested empirical evidence about how variations in a country's competitive and regulatory structure affect bank risk and return. Historically, banking-policy environments in the selected countries differed in four important ways. First, the U.K. had world-class banks and a strong central bank throughout the period of observation. The Canadian and U.S. banking and regulatory environments lag the U.K. in these respects. Second, until relatively recently, the Bank of England tolerated collusive activity and disciplined banks through clubbish moral suasion and informal contacts. Third, efforts to divide reg
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.871 | 0.812 |
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".