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Record W7034523554

Torontoâs Reponse to the Outbreak of War, 1939

2012· article· en· W7034523554 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsWorld War IIMeaning (existential)First world warSpanish Civil WarFront (military)EmpireSpace (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

Canadian historians have paid little attention to the transition from peace to war in late August and early September 1939. Jonathan Vance’s award-winning Death So Noble: Memory, Meaning and the First World War (1997) does a marvelous job of surveying attitudes towards war in the wake of the Great War, but it does not expand into the start of the Second. C.P. Stacey’s official history, Six Years of War, devotes only minimal space to exploring the transition, focusing instead on the activities of Canadian servicemen and women. The dozens of militia histories written by the units after the war dwell on the fighting, not the training.\nAfter telling of the story of Toronto’s experience of the first months of the Second World War, it is possible to reflect on why events unfolded as they did. Community reaction to the transformation of Toronto’s militia force into Canadian Active Service Force (CASF) units provides a window into the world of late August and early September 1939. Through what process did this body of militia men transform themselves into the backbone of First Canadian Army? How many of them volunteered to serve the Empire in the second continental European war in a generation? How did Toronto’s citizens respond to the need to equip another generation of its sons with the tools of war?

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.082
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0240.006
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.001

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 head0.013
GPT teacher head0.210
Teacher spread0.198 · 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
Published2012
Admission routes1
Has abstractyes

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