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Record W4323312751 · doi:10.1111/ssqu.13252

The myth of wartime prosperity: Evidence from the Canadian experience

2023· article· en· W4323312751 on OpenAlexaffabout
Vincent Geloso, Casey Pender

Bibliographic record

VenueSocial Science Quarterly · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsProsperityGreat DepressionFellEconomicsWorld War IIPaceGross domestic productGDP deflatorSpanish Civil WarEconomic historyDevelopment economicsPolitical scienceEconomyEconomic growthGeographyLaw

Abstract

fetched live from OpenAlex

This paper investigates therelationship between prosperity and national account data during wartime, focusing on Canada. In particular, we build off of existing literature arguing that military outlays must be excluded for real output measures to reasonably approximate economic prosperity. We analyse all non‐war components of Canadian gross national product during both world wars and estimate a novel price deflator for World War II in order to take into account wartime price controls. This allows us to obtain a new estimate of real output in Canada excluding military outlays. We then compare the trends in our new real output series with domestic private investment and stock market trends, all three of which either fell or grew at an anemic pace in Canada during both world wars. Combined, we argue that this provides evidence against the idea of wartime prosperity and more specifically, against the notion of World War II ending the Great Depression in Canada.

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)0.015
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0110.007
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.048
GPT teacher head0.258
Teacher spread0.209 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

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