MétaCan
Menu
Back to cohort
Record W2144728873 · doi:10.7202/031076ar

The Crisis in British Army Recruiting in the 1930s

2006· article· en· W2144728873 on OpenAlexvenueno aff
Chris Hull

Bibliographic record

VenueJournal of the Canadian Historical Association · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsPeacetimePrideIncentiveEconomic shortagePolitical sciencePublic relationsPublic administrationLawEconomicsGovernment (linguistics)

Abstract

fetched live from OpenAlex

During the 1930s, the British army suffered a shortage of recruits despite the depression. This study explores the response of the War Office to the crisis, which undermined the army's ability to undertake its peacetime and wartime roles. The study is important in helping to elucidate the army's place in society, as the War Office had to examine itself and its public image to understand the reasons for the shortage. The War Office concluded that its image as a bad employer, an inefficient military force and as the object of pacifist propaganda played a crucial role in deterring recruits. Despite intense, and partially successful, efforts to improve its public relations structure and measures to combat the bad image, the main reasons for the improvement in recruiting from the fall of 1937 were the lowering of the physical standards required of recruits and the improving conditions in the service. The army remained a source of public pride, but one that was separated from society and whose recruits tended to be attracted by economic incentives.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.735

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0190.006
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Canadian Historical AssociationSame topicMilitary History and StrategyFrench-language works237,207