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Arms and the Man: World War I and the Rise of the Welfare State

2004· article· en· W3122367039 on OpenAlexaffabout
Léonard Dudley, Ulrich Witt

Bibliographic record

VenueKyklos · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Policies and Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPeacetimeEconomicsWelfare statePublic goodSuffrageState (computer science)DemocracyWelfareGlobalizationGovernment (linguistics)Political economyMarket economyPolitical scienceNeoclassical economicsPoliticsLaw

Abstract

fetched live from OpenAlex

SUMMARY Why did peacetime government shares of total spending double in a number of Western economies between 1910 and 1938? The widely separated dates for the introduction of universal manhood suffrage and the evidence of a rise in protection during the inter‐war period indicate that neither democracy nor globalization can explain this development. This paper reexamines two other explanations, namely, (1) a shift in the demand for public goods and (2) a war‐induced willingness to share with one's fellow citizens. By introducing into Schelling's (1978) Multi‐Person Dilemma a learning game whose payoffs change endogenously, we provide theoretical explanations for this transformation. We then test the resulting propositions with data on public spending as a share of GNP for the U.S., Canada, the U.K., Germany and Denmark, from the 1870s to the 1930s. In each case, we find no unit root but a break in trend, a result shown to favor explanation (2) over (1).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.185
Teacher spread0.172 · 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 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

Citations15
Published2004
Admission routes2
Has abstractyes

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