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Record W4254951400 · doi:10.1017/9789048521104.004

Dutch Whaling and Sealing in the Seventeenth and Eighteenth Centuries

2008· other· en· W4254951400 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsWhalingHistoryArchaeologyAncient historyArt

Abstract

fetched live from OpenAlex

Introduction Around 1600, while still at war with powerful Spain, an astounding rise in maritime enterprise took place in the young Dutch Republic. In 1602, the Dutch East India Company was established. A few years earlier Dutch mariner Willem Barentsz. tried to find a northeast passage to Asia. During his third attempt in 1596, he and his fellow sailors were forced to winter over on the desolate island of Novaya Zemlya, where he died after having suffered many ordeals. In his earlier voyages to the north, Barentsz. had not only discovered the Spitsbergen archipelago and Bear Island. In his reports on the Arctic, he also mentioned the abundance of seals, polar bears and walruses. Whaling was a maritime enterprise known throughout Europe. Norsemen in the Viking Era hunted whales along shore, developing methods that paved the way for the Basques to carry them out to sea. As early as the twelfth century seafarers from the Basque provinces of southern France and northern Spain had hunted whales. At first these Basque whalemen stayed close to their coast. Later they turned to more remote places, hunting and killing whales off the coast of Newfoundland and Labrador, providing the European markets with valuable products like whale oil and baleen. Arabs of the Caliphate showed keen interest in obtaining narwhal tusks, considered to be an aphrodisiac when grinded and mixed with other foodstuffs. Population rose rapidly around 1600. As a result of these demographic developments, prices of whale products increased dramatically. The number of inhabitants of the coastal province of Holland, for example, rose to 675,000 from 275,000 in 1525. Although natural fats from plants were still available, the demand for substitutes exceeded availability. Changes in agriculture were introduced to the effect that more expensive grains were cultivated, providing more expensive oil. Captains of industries such as rope manufacturing and shipbuilding turned their attention to the oils derived from sea mammals. The first decade of the seventeenth century was an opportune moment for the Dutch to undermine the Spanish whaling activities and undertake means to start whaling themselves.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.017
GPT teacher head0.202
Teacher spread0.185 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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