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Atlantic World 1760–1820

2012· book· en· W2723559637 on OpenAlexaboutno aff
Craig Muldrew

Bibliographic record

VenueOxford University Press eBooks · 2012
Typebook
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsAtlantic WorldColonialismGeographyEmigrationAgricultureInvestment (military)Economic historyConsumption (sociology)EconomyAncient historyHistoryPolitical scienceArchaeologyEconomicsArt

Abstract

fetched live from OpenAlex

There would have been no Atlantic world without trade. Throughout this period, the consumption of American-produced sugar, tobacco, and coffee, as well as the use of American gold and silver for money, was common throughout Europe. At the same time, the settlement of colonial emigrants and transported slave populations continued to grow and to transform the agriculture and environment of the Americas and western Africa. By the mid-eighteenth century the characteristic trading patterns of the Atlantic world were well established. The main exports at the beginning of the period from the New World were gold and silver from the mines of Mexico and Peru, as well as sugar and tobacco grown in Brazil, the Caribbean, and the Chesapeake, together with furs and cod from Canada and forest products from New England. We should not forget that people were also traded; European traders purchased an ever-increasing number of slaves in Africa for export to the Americas. Britain emerged as the dominant trading, military, and investment force by 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0580.029

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 head0.035
GPT teacher head0.246
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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