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Record W2263050030 · doi:10.3138/cjh.ach.50.3.rev14

<i>The Forgotten Majority: German Merchants in London, Naturalization, and Global Trade, 1660–1815</i>, by Margrit Schulte Beerbühl

2015· article· en· W2263050030 on OpenAlexvenueno aff
H. Glenn Penny

Bibliographic record

VenueJournal of History · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNaturalizationGermanEconomic historyPolitical scienceEconomicsInternational tradeLawHistoryArchaeologyCitizenship

Abstract

fetched live from OpenAlex

The Forgotten Majority: German Merchants in London, Naturalization, and Global Trade, 1660-1815, by Margrit Schulte Beerbuhl, translated by Cynthia Klohr. New York, Berghahn Books, 2015. xii, 313 pp. $120.00 US (cloth). This well-researched text has much to teach us about the global systems of trade that developed around London during the early modern period, especially German merchants' impressive roles in those systems. Schulte Beerbuhl came to those insights indirectly. Her interest in naturalization laws revealed a number of surprising facts about the economic functions behind them. For example: allowing foreigners living abroad to become British subjects proved to be highly advantageous for both those foreigners and the British. In turn, her exploration of such facts exposed a forgotten majority of German merchants in London and abroad who played critical roles in expanding that city's global markets. At the same time, the lives of those merchants now teach how tightly intertwined immigration, naturalization, and individual merchants' interests were during the period in which Great Britain's empire became global. Anyone with an interest in naturalization laws or trade networks will profit from reading this book. So too will individuals who would like to know more about Anglo-German trade in the seventeenth century or the development of eighteenth-century German trading houses. Many scholars will also benefit from her revelations about the ways in which Germans became critical to London's trade with Russia, the importance of which has been largely obscured by our focus on British trade networks spanning the Atlantic, reaching into the Mediterranean, and extending as far as China and India. Russia, she reminds us, played a critical role in supplying industrializing England with raw materials, such as flax, hemp, and timber, and German merchants were essential to that trade. In part, the role of German merchants in building trade with Russia and other places came about as a result of trading patterns and cultural practices established by the Hansa cities. Germans were already well integrated in Russian trade by the time the British Empire began to grow. They were conversant in local customs as well as the Russian and German languages, and many German merchant families had established households in Moscow and later St. Petersburg, not to mention the Baltic States. British merchants, in contrast, were newcomers in those territories, and few were interested in staying in those locations for extended periods. As a result, after the signing of the 1734 trade agreement between Russia and Great Britain, naturalizing German merchants who had family connections in those areas, ties to Russia's political and commercial elite, as well as stores of local knowledge made good business sense. …

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: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.028
GPT teacher head0.227
Teacher spread0.199 · 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
GenreReview

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
Published2015
Admission routes1
Has abstractyes

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