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Record W6936549819 · doi:10.58066/v402-0f13

Fitch, Burton: my wartime experiences (February 2, 2007)

2007· other· en· W6936549819 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2007
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWifeInfantryDutyWorld War IISpanish Civil WarDaughter

Abstract

fetched live from OpenAlex

ABSTRACT: Burton Fitch Burton was born in Quebec City. At age 5, his family moved to Montreal. Burton joined the Canadian Infantry Corps in 1942. At the age of 27 he was at least 5 years older than all the other platoon commanders. He was also married and soon had a new son. Burton joined because he resented the death on duty of his good friend, and felt he would be called up eventually. After training in St Jerome, Brockville and Valcartier, he was sent to serve in Northwest Europe. Burton took part in battles in Boulogne, Cap Gri Nez, 25 harrowing days in the Sheldt (Holland and Belgium), and crossing the Rhine. When the war ended, he stayed in Europe with the Occupation Forces for one year. In 1946, Lt. Fitch was demobilized. He returned to his family in Montreal and made his career as an insurance broker. Burton's message for our youth today is 'There comes a time when you have to go to war'. Burton has been retired in Nanaimo since 1984. Rabbi Cass, Canadian Army Chaplain, arranged for Burton to attend a Passover seder with a family in England. The father contacted Burton and told him he had a daughter Burton's age. Burton answered 'I have a wife your daughter's age', and he didn't attend the seder. "One of the remaining memories of the Scheldt is that the 25 days that I served there, I had two pairs of socks and one bath. This was not one of the more pleasant memories." "The men were indescribably dirty, they were bearded, cold as it is only possible to be cold in Holland in November, and wet from having lived in water-filled holes in the ground for twenty-four hours a day. Their eyes were red-rimmed from lack of sleep, and they were exhausted from their swift advance on foot under terrible conditions. Yet all ranks realized with a certain grim satisfaction that a hard job had been well and truly done."

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.003
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0680.011

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.

Opus teacher head0.026
GPT teacher head0.282
Teacher spread0.257 · 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
Published2007
Admission routes1
Has abstractyes

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