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Record W4296472170 · doi:10.1093/ahr/rhac152

Base Money

2022· article· en· W4296472170 on OpenAlexaff
Jeong‐Min Kim

Bibliographic record

VenueThe American Historical Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMonetizationBlack marketCurrencyPaymentSpanish Civil WarCirculation (fluid dynamics)CommodityCustomer base

Abstract

fetched live from OpenAlex

Abstract This article discusses how US military payment certificates (MPC) escaped from US military bases during the Korean War to become common currency in local economies. The MPC program was intended to control the mixing of US currency in local economies, yet the worldwide use of MPC on all overseas US bases between 1946 and 1973 facilitated black market circulation of military notes globally by allowing trading differentials among dollars, MPC, and local currencies. As soldiers, goods, and money moved through the US base network across Korea and Japan during the war, MPC were commonly used as a medium of exchange for sexual transactions between US soldiers and local women in both countries. The cross-border sexual markets were central to the everyday economies of Korea and Japan, of which black markets trading US Army supplies and currencies were major components. An analysis of this off-base monetization process of MPC offers a new perspective on the global history of war and occupation by highlighting how the sexual economy of illicit and informal transactions has been integral to US military expansion abroad since the end of World War II.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.117
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1170.031

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 head0.035
GPT teacher head0.301
Teacher spread0.266 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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