Bibliographic record
Abstract
‘Everybody I meet seems vaguely alarmed that something terrible is going to happen financially.’ So wrote Winston Churchill from Biarritz to Eddie Marsh on 7 August 1931, adding: ‘I hope we shall hang Montagu Norman if it does. I will certainly turn King’s evidence against him.’1 Eight days later, Norman, the Governor of the Bank of England, left Britain by boat for Canada. He did not depart to evade the hangman, but because he had experienced yet another of his mental collapses, and he had been ordered by his doctor to rest. Norman was to be away for over six weeks during which time the financial crisis deepened, and the ‘something terrible’ that he must have dreaded took place. His colleagues at the Bank tried to warn him of the announcement to be made on 20 September 1931, and of the legislation which, of necessity, followed the next day, but, as Norman made his homeward journey, they had no means of contacting him in confidence. ‘Sorry to go off before you arrived’ proved to be a message that did not convey the news to Norman. It was only when he reached the port of Liverpool that Norman learnt to his dismay that what was officially described as the suspension of the Gold Standard had taken place.2 The Gold Standard (Amendment) Act of 1931 marked the end of an era that dated back to the Armistice in 1918. For no longer was the British political nation dominated by the sentiment of going ‘back to 1914’.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.040 | 0.014 |
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".