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Record W2799047912

Soldiers of Song: The Dumbells and Other Canadian Concert Parties of the First World War

2012· book· en· W2799047912 on OpenAlexaboutno aff
Jason Wilson

Bibliographic record

VenueThe Atrium (University of Guelph) · 2012
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsWorld War IIHistoryPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

To optimize the fighting potential of Canadian soldiers in the First World War, organized 'concert parties' of the Canadian Expeditionary Forces (CEF) satisfied an official military mandate of raising the morale of Canadian soldiers. Ironically, concert party performers were able to achieve this aim by mocking the military system and its high ranking officers. Many officers were aware of the subversive material found in the concert parties' performances, but chose to ignore it, because of its positive effect on troop morale. The comedic material of both Canadian and British concert parties transformed over the course of the war from the light fare offered in the British Music Hall, to a darker humour that was 'exclusive' to Frontline soldiers. The exclusive nature of soldier humour was not only effective in raising the morale of the troops, but also forged an enduring and vital bond between soldier-entertainers and their audiences. Following the war, civilian audiences were introduced to the Dumbells and their sardonic interpretation of the 'Great War', largely through those soldiers who had seen the concert party perform in France. Among the pioneers of sketch comedy, the Dumbells are as important to the history of Canadian theatre, as they are to the country's social and cultural history. If nationhood was won on the crest of Vimy Ridge, it was the Dumbells who provided the country with its earliest soundtrack.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.192
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2012
Admission routes1
Has abstractyes

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