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Record W2971832883 · doi:10.3138/cjh.ach.2018-0044

Contesting Urban Space between the Dutch and the Sultanate of Yogyakarta in Nineteenth-Century Indonesia

2019· article· en· W2971832883 on OpenAlexvenueno aff
Purnawan Basundoro, Linggar Rama Dian Putra

Bibliographic record

VenueJournal of History · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismIndonesianPoliticsSpace (punctuation)Power (physics)Political scienceUrban spacePolitical economyEconomySociologyGeographyHistoryEconomic geographyLawEconomics

Abstract

fetched live from OpenAlex

This article focuses on the historical construction of what has recently been understood as the urban space of Indonesian colonial cities. Although studies on this topic have been carried out within various contexts, scholars generally take the concept of urban space for granted as a means to expand their arguments. Moreover, since the historical evidence shows that the domination of colonial power is contingent on several conditions including the economy, military actions, and local politics in the colonies, it becomes necessary for academics to reconceptualize Indonesian colonial urban histories. In this matter, the reconceptualization calls for more explanation of how colonial urban space was created during early colonial times in which the socio-political foundations of colonialism took place. This study traces the history of the city of Yogyakarta, Indonesia, in the nineteenth century, and examines the transformation of urban space during the colonial conflict between the Dutch and the Kingdom of Yogyakarta. Economic, military, and political conditions shaped the development of urban space of Yogyakarta. The city was deeply influenced by Dutch colonial policies, including the introduction of colonial norms and values in an engineered urban space.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.238
Teacher spread0.224 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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