MétaCan
Menu
← Back to cohort
Record W6926751989 · doi:10.25446/oxford.25933615.v1

Breaking Down Social Barriers: The Home Guard

2024· other· en· W6926751989 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
Fundersnot available
KeywordsGuard (computer science)GermanNational guardQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Jack Ford had been a conscript in the "First War" and at 41 years old in 1940 was deemed too old to be called up again, so joined the Home Guard in Rochdale. Having been trained in the use of a rifle he was able to tutor some of the less experienced members. These included Jim Welburn, a millowner (the contributor was told) from Norden, who befriended Jack. Jack was a window cleaner, so their paths would not have normally crossed in peacetime. Jim discovered that Jack's son, Brian, was planning to study English at university towards the end of the war. His wife, Emily, had studied English in Manchester about 30 years earlier. They gave Brian some of her books, which are still kept by the contributor. Apart from cementing social cohesion, life in the Rochdale Home Guard was largely uneventful. Jack related one particular story to the contributor. Avro Lancasters were manufactured in Chadderton between Oldham and Manchester. German pathfinders would drop flares on the moors outside Rochdale to guide the way for bombers to attempt to destroy the factory. The local Home Guard armed with buckets of water would douse the flares to foil the Luftwaffe. They also serve who carry buckets of water!

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)0.003
metaresearch head score (Gemma)0.004
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 score0.035
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0200.009
Scholarly communication0.0060.007
Open science0.0010.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0210.003

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 head0.242
Teacher spread0.228 · 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

Explore more

Same venueFigshare→Same topicAquaculture disease management and microbiota→French-language works237,207→