<i>The Spirit of the Blitz: Home Intelligence and British Morale, September 1940–June 1941</i>, ed. Paul Addison and Jeremy A. Crang
Bibliographic record
Abstract
There are few events over which historians have spilled as much ink and which also resonate as strongly in British public memory as the Blitz. Whether the German bombing campaign against London and other British cities during the Second World War united or divided the British people, and to what extent the bravery and defiance exhibited in the so-called ‘Blitz spirit’ was a social reality or a myth, have been continuously debated and deconstructed across the eight decades since. In this volume, edited by the late Paul Addison and Jeremy A. Crang, readers are given the opportunity to experience those difficult and dramatic months through the words, thoughts, and feelings of the people who lived them. A sequel to their 2010 volume, Listening to Britain: Home Intelligence Reports on Britain’s Finest Hour, May to September 1940, the book is a compilation of the reports created by Home Intelligence (HI), a unit of the Ministry of Information (MOI) charged with monitoring and assessing the morale of the British people, from when the first bombs fell on London through the invasion of the Soviet Union. Although they were highly mediated and the product of less than scientific research methods, the editors argue that ‘Whatever their limitations, the reports are the closest we are ever likely to get to the truth about morale and public opinion in wartime Britain’ (p. xxviii).
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".