MétaCan
Menu
Back to cohort

‘Measuring by the bushel’: reweighing the Indian Ocean pepper trade

2010· article· en· W1606155343 on OpenAlexaff
Sebastian R. Prange

Bibliographic record

VenueHistorical Research · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBushelPepperIndian oceanBusinessHorticultureEnvironmental scienceAgricultural scienceOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

Of all the oriental spices, black pepper was the most important until the eighteenth century. The historiography of the pepper trade is characterized by a strong focus on Europe in terms of both its economic significance in the ancient and medieval periods and the struggle for its control in the early modern period. This article, by contrast, seeks to situate the pepper trade firmly in its Asian contexts. It examines the Indian Ocean pepper trade from three perspectives. First, it places the trade in its supply-side context by focusing on the Malabar coast as the primary source of pepper. Second, it examines the relative importance of the different branches of Malabar's pepper trade and highlights the central role played by Muslim mercantile networks. Third, it considers the reconfiguration of these pepper networks in the sixteenth century in the face of aggressive competition from the Portuguese. In their sum, these arguments advocate the need for rethought balances of trade and a reweighted scholarly focus on the pepper trade in its global dimensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.009
Scholarly communication0.0060.008
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.231
GPT teacher head0.276
Teacher spread0.045 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations43
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueHistorical ResearchSame topicGlobal trade and economicsFrench-language works237,207