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Record W2167967275 · doi:10.20495/seas.2.3_475

The Long-term Pattern of Maritime Trade in Java from the Late Eighteenth Century to the Mid-Nineteenth Century

2013· article· en· W2167967275 on OpenAlexaboutno aff
Ryūtō Shimada

Bibliographic record

VenueSoutheast Asian studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)JavaIndigenousCultivation SystemPeriod (music)HistoryEconomic historyAncient historyEconomyEconomicsArchaeology

Abstract

fetched live from OpenAlex

This article investigates the trade pattern of Java from the late eighteenth centur to the mid-nineteenth century from a long-term perspective. There is no comprehensive data on Javanese trade during the period in question, with information on local and regional trade being particularly scarce. To fill in the missing pieces and identify a broad trend, this paper attempts to examine data on both the late eighteenth century and the second quarter of the nineteenth century and put them together with the scattered data available on the first half of the nineteenth century.This paper suggests, first, that while it is known that Java's economic relations with the outside world were heavily oriented toward trade with the Netherlands, this trend began in the late eighteenth century rather than with the introduction of the Cultivation System in 1830. Second, Java's coastal trade also began to develop in the late eighteenth century. This trade was conducted by European traders and Asian indigenous traders, including overseas Chinese traders settled in Java.Third, trade with the Outer Islands declined in the late eighteenth century but resumed its expansion in the second quarter of the nineteenth century. Fourth, intra-Asian trade with the region outside insular Southeast Asia declined in the long run, along with the decline and bankruptcy of the VOC, which had successfully engaged in this branch of intra-Asian trade since the seventeenth century.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.262
Teacher spread0.245 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations8
Published2013
Admission routes1
Has abstractyes

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