George Ryall's wartime experiences including Dieppe and being a PoW
Bibliographic record
Abstract
This is the story of Gordon Ryall. He was born in 1923 in Croydon. He was a good swimmer which was to hold him in good stead in the future. He enlisted in the navy aged just 15, lying about his age. At the Battle of Dieppe in 1942, he was a Royal Navy telegraphist attached to the Royal Hamilton Light Infantry. On landing at Dieppe, he was told to crawl up the beach, steal a car, communicate with a British destroyer and get them to fire onto enemy lines. He was with a Canadian group of soldiers. The attack was unsuccessful and he was captured and spent 3 years as a prisoner of war. He was in Stalag 344. His prison number was 26488.In 1972, the BBC produced a documentary about Dieppe, 1942. This is Gordon Ryall's account of his wartime experiences.In the early weeks of August 1942, when I was stationed in HMS Dundonald II, the base of 'Combined Operations', we were ordered to prepare ourselves for draft to an unknown destination. At five o'clock one evening, we moved out our kitbags and piled both the kit and ourselves onto a waiting lorry and moved off, bound for where—we did not know.We boarded the train for London, travelling in moderate comfort and arrived at Euston at about eight o'clock in the morning, just in time for breakfast. After breakfast, we all mustered outside the station and boarded the waiting buses.Just after midday, we arrived at our destination. This was a small village (I believe Fleet) about five miles outside Aldershot. When we had been there for about two days, we were told that we were there to give a demonstration to the Americans... this we didn't believe. In order to hide our purpose of our billet in this village from the civilians, it was suggested that we let slip information that we were survivors from a shipwreck recuperating before returning to sea. It needs little imagination to see the picture of the 'yarns' told by the 'locals' in the evenings. I must admit that some of the stories told were completely beyond belief, but the locals bought the beer and we were treated like royalty.The fortnight that followed was in effect a rest period but on 18th August action started. Our names were called out—we proceeded to the stores to draw the radio sets, revolvers, and ammunition. We were joined by the officers and after boarding the lorry, started off to Southampton.En route we had the first sight of something wrong, the convoy was split and we appeared to have lost the way. We stopped for some time and I learnt that the officer from the Intelligence Corps, who was map reading, had lost his bearings. A fine start I thought. For some time, there was an argument over which road to take. Eventually it was decided that the driver should be allowed to take his own route and we arrived safely in Southampton Dockyard and embarked onto the waiting ship and went down to the mess to receive our orders.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.018 |
| Insufficient payload (model declined to judge) | 0.012 | 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".