The Life and Mysterious Death of Poet and Intelligence Agent Stephen Haggard, 1911-1943
Bibliographic record
Abstract
Actor, memoirist, novelist, playwright and poet, Stephen Haggard was a highly individual figure in the English literature and theatre of the 1930s and Second World War. Haggard was born in Guatemala City in 1911, the son of a British colonial officer – who was a nephew of H. Rider Haggard – and his French-Canadian wife. He died in mysterious circumstances in 1943 while serving with British Army Intelligence in the Middle East. This biography retraces Haggard’s brief yet vivid and crowded life and work. From a colonial childhood and education in England, the story moves on to prewar theatre studies in Munich, stardom on the London and New York stages and from there to service with the Army, the BBC, the Special Operations Executive and its rival Political Warfare Executive. The author shows that Haggard felt verse to be his vital outlet, artistic and emotional, although he did not seek publication until the outbreak of Hitler’s war. Wartime poems such "The Tear" and "Lotus" struck a chord with the many other young men and women who had to set aside civilian life, and Haggard's widow Morna collected the verse for publication with his memoir I’ll Go to Bed at Noon (1944). In this book, Ross Davies traces a fascinating life story that has been largely lost from view and makes a convincing case for Haggard's important contribution to the interwar literary and cultural scene.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".