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Record W6926851461 · doi:10.25446/oxford.25933375.v1

Rural childhood life during WWII

2024· other· en· W6926851461 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldMedicine
TopicActinomycetales infections and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsButcherWorld War IISisterSpanish Civil WarDaughterFirst world war

Abstract

fetched live from OpenAlex

We lived on a smallholding called Caledon Cottage, Common Lane, Corley Moor, next door to the Bull and Butcher pub.I was the second daughter of Arthur Samuel and Lydia Marriott (nee Ashby).My elder sister was Joy Margaret Marriott, who was 21 months older but is now deceased.The property was a cottage surrounded by fields and we had lots of hens, ducks, pigs and dogs.We used to walk to school in Corley, 2 or 3 miles, to get to school.Mother had TB and died when I was 7, but Dad was like Mum and Dad to me.When WWII broke out Mum was in a sanitorium in Warwick, but it had to be vacated for the war effort.Dad converted an outbuilding to keep Mum separate from us.Dad was in WWI for 4 years and was gassed in the trenches; his stomach lining was destroyed.When WWII broke out I wondered what was going to happen and he took me to one side and explained. When Coventry was blitzed in April Dad took us up in a high field and we saw the 'planes flying over and the fires.When food became scarce we were OK as father had a large garden and an orchard; we had ration books, but for milk and eggs we were self-sufficient. Our neighbours gave us each a calf; Joy's was called Mary Anne, mine was Dolly Dimple, but they had to be slaughtered when they got older.We were very lucky to live in a village where people kept an eye on us.We didn't really need toys, but we had a see-saw and a sandpit.Dad worked for W.H.Jones Builders in Coventry; on my birth certificate he was described as a scaffolder, but later he became a foreman and then he was Clerk of Works for Warwickshire County Council.After Mum died Aunt Nellie, who had been widowed in WWI, looked after us and we had a bed in her house. There was a woman who worked at the same company as Dad, a cashier, who Dad known since they were young, Edith Esther North, and she was from Bell Green, Coventry. They got married in 1942 or so and we left Corley Moor and moved to Brownshill Green; Joy went to school in Coventry, while I went to Corley Moor C of E school.Edith became our second Mum.Whatever happened Dad looked after us and made sure we understood why we couldn't have new clothes without coupons.We were never bombed out, but the gas works about 3 miles away was attacked and an unexploded bomb was brought to the common to be disposed of.We were walking home from school and jumped into the hedge, as we'd been told to.My husband was 15 years older than me and had served in the RAF as a navigator; we met when we worked together at Courtalds.He'd trained in America and Canada.I remember walking through rubble to go to school for several years.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0230.004
Scholarly communication0.0060.003
Open science0.0010.008
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0360.009

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.

Opus teacher head0.014
GPT teacher head0.261
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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