Harold Daniels in the Fleet Air Arm
Bibliographic record
Abstract
Harold joined the Royal Navy on 06/02/1940, aged 15. He gained an apprenticeship with the Royal Navy but trained with the RAF prior to going into the Fleet Air Arm. He worked in electrical and ordnance duties on the aircraft.He was sent to RAF Halton for training. He was sent to New York on the Queen Elizabeth on 19/11/1943; it was his birthday on the day he arrived. From New York, he went to an air force base near Boston to form up 853 Avenger Squadron, a torpedo/bomber/fighter unit that, Harold says, was 'way ahead of its time'. The squadron was formed from November 1943 to February 1944.From Boston, he was sent to Vancouver, Canada. On the journey, you had to amuse yourself across the USA. Harold and a Yorkshire friend gambled all the way across.At Vancouver, he joined the HMS Arbiter and sailed down from Vancouver to the Panama Canal. There was an accident at sea. On the boat, a plane crashed off the deck on a training flight, and the pilot was killed. He escorted a convoy back to England after the Panama Canal. He was then at the Orkneys with his ship until 13/09/1944.Then, the squadron picked up HMS Tracker. This was a convoy bound for the USSR. The boat went to Murmansk, where it was very cold. There were very rough weather conditions on the way. There was lots of US Lend-Lease equipment there, including American Jeeps. His experience with Soviet troops and people was positive. He got back to the Orkneys and was there from 05/12/1944 to 25/01/1945. He then joined HMS Queen.Harold served with the Fleet Air Arm and left on 19/11/1964. After the war, Harold served with the Royal Australian Navy and visited Japan (Hiroshima) and all over Australia. The Australians were starting a Fleet Air Arm, and Harold was sent to help them set it up. There were differences between the Australian and British Navy; for instance, Australians did not address people by their surnames.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.099 | 0.036 |
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".