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Record W3122098230

After the War Boom: Reconversion on the U.S. Pacific Coast, 1943-49

2003· preprint· en· W3122098230 on OpenAlexaboutno aff
Paul W. Rhode

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBoomDemobilizationShock (circulatory)World War IIEconomicsQuarter (Canadian coin)EconomyGeographyPolitical scienceEngineeringPolitics
DOInot available

Abstract

fetched live from OpenAlex

During the Second World War, the American Pacific Coast experienced a tremendous economic boom fueled by disproportionately large flows of military spending. Even before the conflict's end, fears spread that the region's postwar economy would not provide sufficient jobs for its greatly enlarged labor force. Responsible authorities predicted one million workers one-quarter of the labor force would be unemployed one year after demobilization. But the conversion experience over the 1945-49 period proved far easily than anticipated, a finding which this paper attributes to strong home market effects' highlighted in the new Economic Geography literature. Based on an empirical investigation of the long-run relationship between manufacturing production and the size of the Pacific region's market, this study finds support for the views that the region's economic structure could support multiple equilibria and that the transitory shock of military spending during World War II helped push the Pacific Coast economy from a low-level' equilibrium to a higher-level' equilibrium consistent with the same fundamentals.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.255
Teacher spread0.210 · 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
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

Citations2
Published2003
Admission routes1
Has abstractyes

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