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Record W1994101751 · doi:10.7202/031107ar

Mobilising Canada: The National Resources Mobilization Act, the Department of National Defence, and Compulsory Military Service in Canada, 1940-1945

2006· article· en· W1994101751 on OpenAlexvenueaboutno aff
Daniel Byers

Bibliographic record

VenueJournal of the Canadian Historical Association · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMilitary serviceMobilizationNational servicePoliticsPublic administrationAdministration (probate law)Context (archaeology)Government (linguistics)Political scienceResistance (ecology)Service (business)Military personnelWorld War IILawHistoryEconomyEconomics

Abstract

fetched live from OpenAlex

Compulsory military service took on the most organized, long-term form it has ever had in Canada during the Second World War. But few historians look beyond the politics of conscription to study the creation, administration or impact of a training system that affected more than 150,000 people. Faced with the Mackenzie King government's policy of conscripting manpower only for home defence, and their own need for overseas volunteers, Army leaders used conscripts raised under the National Resources Mobilization Act to meet both purposes. This paper explores the Army's role in creating and administering the compulsory military training system during the war, the pressures put on conscripts to volunteer for overseas service, and the increased resistance to volunteering that resulted by 1944. The consequences of the Army's management of conscription came very much to shape the political events that took place in 1944, and cannot be fully understood outside that context.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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 designNot applicable
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

Citations39
Published2006
Admission routes2
Has abstractyes

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