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Record W4402484691 · doi:10.1177/08438714241272611

Is the <i>SlaveVoyages</i> database useful for scholars of slave trading in the wider Indian Ocean World?

2024· article· en· W4402484691 on OpenAlex
David Eltis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Maritime History · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndian oceanChinaDesert (philosophy)World tradeAtlantic WorldFur tradeGeographyAtlantic slave tradePacific oceanOld WorldWorld historyHistoryOceanographyPolitical scienceAncient historyEconomic historyInternational tradeArchaeologyBusinessGeologyLaw

Abstract

fetched live from OpenAlex

Assessing the differences between scholarly collaboration on slave trading in the Atlantic World, on the one hand, and similar activities in the wider Indian Ocean, on the other, needs to begin with an assessment of the relative importance of slave trading in the two oceans. Both oceans saw a maritime slave trade that drew heavily on sub–Saharan Africa. But while almost all captives arriving in the Americas came from Africa, in the Indian Ocean World there was a significant, probably majority, traffic in non-Africans, especially if one includes the South China Sea, as indeed most assessments of the Indian Ocean World slave trade do. Focusing on Africa alone initially, scholars who have made their name in the Atlantic World have tended to support the idea that the combined numbers of the Sahara Desert and Indian Ocean slave trade over two millennia were about the same as the volume of the transatlantic slave trade in its 360 years of existence.

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.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.486

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.304
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