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Record W7036664309

Combat Motivation and Swift Trust in Canada's Battle of Hong Kong, 1941

2025· article· en· W7036664309 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsnot available
Fundersnot available
KeywordsBattleCohesion (chemistry)SwiftBattlefieldMultinational corporationOdds
DOInot available

Abstract

fetched live from OpenAlex

Abstract: In December 1941, the British Crown Colony of Hong Kong was the site of a doomed last stand, when the Imperial Japanese Army assaulted the British enclave near-simultaneously with the strike on Pearl Harbor. Among Hong Kong’s multinational defenders were two battalions of Canadian infantry, designated “C Force.” They held out for a significant period and inflicted heavy casualties upon the Japanese, despite the fact that the Canadians were under-trained, under-equipped and fighting a battle that could not be won. This article is the first major study of combat motivation in the Battle of Hong Kong, taking the Canadian C Force as a case study. It explores the training, morale, cohesion and behaviour of the Canadians who fought this hopeless battle. This article argues that the concept of “swift trust” cohesion can explain how the Canadians fought so well against impossible odds at Hong Kong, even when primary group cohesion became impossible to sustain during battle.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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