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Record W4315629335 · doi:10.26443/jiows.v6i2.139

Children on Board: Child labor on ships in the Indian Ocean, c. 18th – 19th Centuries

2023· article· en· W4315629335 on OpenAlexvenueno aff
Sundara Vadlamudi

Bibliographic record

VenueThe Journal of Indian Ocean World Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
Fundersnot available
KeywordsSophisticationIndian oceanWork (physics)On boardService (business)Child labourScope (computer science)HistoryPolitical scienceEconomySociologySocial scienceEngineeringEconomicsOceanographyArchaeology

Abstract

fetched live from OpenAlex

A growing body of research has focused on adult Asian sailors’ employment on European ships in the Indian and Atlantic Oceans. However, the experiences of children who worked on ships in the Indian Ocean World have received comparatively little attention. The scholarly lacuna is striking considering the tremendous increase in the scope and sophistication in the discussions on child slavery and abolition. This article examines the use of children as maritime laborers in the Indian Ocean World between the late eighteenth and nineteenth centuries. In doing so, it examines the multiple pathways through which children were brought for work on ships and studies the recruitment patterns of adult and child sailors. It focuses on the various types of labor performed by children on ships and discusses how conditions of servitude on land were transferred to a ship when children accompanied their masters. It then also discusses how prevailing understandings of childhood, domestic service, and child labor shaped the actions of English East India Company officials towards child sailors while undertaking anti-slavery measures during the nineteenth 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)0.003
metaresearch head score (Gemma)0.001
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 score0.432
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.293
Teacher spread0.274 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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