Bibliographic record
Abstract
Florance and Jack were my parents. At the same time, Florance's sister, Mary, got married at the same time. They had a double wedding.The week after the wedding, Jack had to go into the fire service and Frank Lewis, my Uncle Frank, was sent to make tanks. He wanted to go into the navy, but he had to make tanks because he was a moulder. They wouldn't let him join the navy.Savile Hodgson was Jack's best man. He went into the army. James Helliwell was Frank's best man. He went into the navy. As far as I know, he was on the Russian convoys. Frank Edward, I think he was an usher. This is Tommy, Frank's brother. He was in the Navy. On my dad's side. That's George. I think he was in the army but it could have been the air force but I'm not sure.They all came back from the war. At one time they thought James had died because all his letters came back. That's how they found out that he was on the Russian convoys; because they couldn't have letters. He was a stoker as well. His uncle had been a stoker in the First World War. Fred Hainsworth. And he'd told him so many tales of being a stoker that he said he was going to be a stoker. They said "We don't usually get that" we usually have to make people be stokers."Another photo - That's my dad and the lady next to him came from Plymouth or Southampton. When they were badly bombed, they had to be evacuated and I think they were told they had to take somebody. I don't know her name and they never heard from her once she went back. All these soldiers were from Dunkirk, and they were billeted with my grandma. That's my Auntie Mary again. I think all three were with my grandma.Another picture of Halifax Fire Service - My dad is the smallest one.Another one - this is Manor Heath Park at the bottom of "The Moor." They were billeted somewhere in the grounds at Manor Heath Park to start with. I know they were up Hanson Lane so this looks like it was earlier. At one point my dad had to go to Liverpool after all the heavy bombing there. And he also went to Birmingham. One time they were told they had to take a fire engine "I don't know whether that was Liverpool or Birmingham. They were told not to follow any red lights.Another photo - this was my Auntie Emmy. She was married then and they'd just gone to the pictures and when they got back home all the windows were out because they lived up in this area. And then another time, incendiary bombs were dropped at King Cross. There used to be a laundry at King Cross, next to where that grass is. It was in that area. And that bomb I brought is from that.And this one is St Mark's Church where my mum and dad got married. Here is the Sunday School and at one point soldiers were billeted there. There was a lot of "at this ground here" they marched and paraded. But I just know which part of the war or whether it was all the time.Ration books - 1 for me, 1 for Florance and 1 for Dad. These were after the war because we were still using them into the 50's.National Registration ID cards.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.011 |
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".