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Record W4403297482 · doi:10.26443/jiows.v8i1.176

Slaving, Colonial Diplomacy, and Resource Extraction in Seventeenth-Century Maritime Asia

2024· article· en· W4403297482 on OpenAlexvenueno aff
Hans Hågerdal

Bibliographic record

VenueThe Journal of Indian Ocean World Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
Fundersnot available
KeywordsDiplomacyColonialismResource (disambiguation)HistoryAncient historyEconomyPolitical scienceArchaeologyEconomicsComputer scienceLaw

Abstract

fetched live from OpenAlex

This study combines perspectives of social change and resource exploitation from two angles: the intercultural diplomacy conducted by the VOC in early modern maritime Asia, and the trajectories of slavery, slave routes, and zones of coerced labour in this macro-region. The use of enslaved people by European polities for production of cash crops and domestic work in maritime South and Southeast Asia has been widely researched. The local consequences of the widespread slaving need however to be better understood, not least in terms of the exploitation of natural resources and their entanglement with social change in the affected areas. The article discusses how early colonial diplomacy and treatymaking with indigenous societies in the period 1600-1700 had a role in shaping slave circuits while impacting on local economic systems. A combination of slaving and extraction of commercial items of ‘luxury’ type is often found in the diplomatic instruments. The study highlights the possibilities of Dutch contracts and agreements to trace historical processes in combination with other types of sources. By looking at negotiating practices, we can better understand the structures of geographical distribution of slaving activities, trading practices, forced deliveries of manpower, and resistance to enslavement. In sum, the consequences of enforced movement of people in the contact zones between colonial and indigenous groups.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.314
Teacher spread0.299 · 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 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
Published2024
Admission routes1
Has abstractyes

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