Kevin Quinlan.<i>The Secret War between the Wars: MI5 in the 1920s and 1930s</i>.
Bibliographic record
Abstract
This study is a welcome contribution to the growing literature on the secret activities of the British state in the interwar period. As Kevin Quinlan quite rightly observes, there was a war that was waged between the Great War and World War II and in Britain’s case much of this was done in secret by the underpowered, but growing British secret state. Quinlan also suggests that this was the era when ideologies and popular forces that had been held at bay up until 1917 broke through to control state power, first in Russia, and then in Italy and Germany, which created challenges for the British state reminiscent of the current obstacles faced by the American War on Terror today. The Secret War between the Wars: MI5 in the 1920s and 1930s focuses on the role of MI5 in this secret war. Quinlan’s doctoral work at Cambridge University, and his participation in its important seminar on intelligence history served as the impetus for this book. Those new to this field will find the early section on the structure of the British intelligence establishment and its key early players useful, but the real strength of the work is on aspects of MI5 tradecraft that are highlighted by chapters based on a close reading of British National Archives files and offered in the form of thematic case studies. At times one wonders if the British spy fiction writer John le Carré did not help with the titles of these chapters (though he does find himself on the pages nonetheless) with themes such as “Official Cover,” “Counter-subversion,” “Recruitment and Handling,” “Penetration Agents,” and “Defection and Debriefing.” These are all ingenious ways to introduce the topics covered in each chapter.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".