The Final Demise of Unfair Debtor Discrimination?- Comments on Ms Krueger's Speeches*
Bibliographic record
Abstract
During the last few weeks of the year 2001 a fairly old proposal to solve the debt crisis of Southern countries has regained momentum – applying the principles of domestic insolvency proceedings to sovereign states. Anne Krueger's (2001a, 2001b) recent speeches proposing to "mimick " domestic insolvency laws are a very useful contribution to the issue of debt mana-gement. Her first speech in Washington seems to have been the one falling stone taking the whole stonewall with it. Eventually this economically sensible idea has gained street credibi-lity in Wall Street. The taboo of discussing insolvency is finally overcome. Anne Krueger's speech in November 2001 followed several statements in favour of sovereign insolvency. The Secretary the US Treasury, Paul O’Neill, was the first influential politician publicly confirming the usefulness of an international insolvency procedure for sovereign governments. This idea was seconded by the British Chancellor of the Exchequer, Gordon Brown, and the Canadian Finance Minister, Paul Martin, a bit later. In a recent paper two em-ployees of the Bank of England and the Bank of Canada, Andy Haldane and Mark Kruger (2001, p.13), propose a standstill arguing that sovereign debtors need the safe harbour which bankruptcy law provides in a corporate context: "Everyone accepts this as an important part of
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.061 | 0.047 |
| Insufficient payload (model declined to judge) | 0.025 | 0.018 |
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".