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Fur Trades

2016· reference-entry· en· W4245089614 on OpenAlexaffabout
Carolyn Podruchny, Stacy Nation-Knapper

Bibliographic record

VenueOxford Research Encyclopedia of American History · 2016
Typereference-entry
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsIndigenousClothingGeographyFur tradeEconomyColonialismInternational tradeBusinessEconomicsEcologyArchaeology

Abstract

fetched live from OpenAlex

Abstract From the 15th century to the present, the trade in animal fur has been an economic venture with far-reaching consequences for both North Americans and Europeans (in which North Americans of European descent are included). One of the earliest forms of exchange between Europeans and North Americans, the trade in fur was about the garment business, global and local politics, social and cultural interaction, hunting, ecology, colonialism, gendered labor, kinship networks, and religion. European fashion, specifically the desire for hats that marked male status, was a primary driver for the global fur-trade economy until the late 19th century, while European desires for marten, fox, and other luxury furs to make and trim clothing comprised a secondary part of the trade. Other animal hides including deer and bison provided sturdy leather from which belts for the machines of the early Industrial Era were cut. European cloth, especially cotton and wool, became central to the trade for Indigenous peoples who sought materials that were lighter and dried faster than skin clothing. The multiple perspectives on the fur trade included the European men and indigenous men and women actually conducting the trade; the indigenous male and female trappers; European trappers; the European men and women producing trade goods; indigenous “middlemen” (men and women) who were conducting their own fur trade to benefit from European trade companies; laborers hauling the furs and trade goods; all those who built, managed, and sustained trading posts located along waterways and trails across North America; and those Europeans who manufactured and purchased the products made of fur and the trade goods desired by Indigenous peoples. As early as the 17th century, European empires used fur-trade monopolies to establish colonies in North America and later fur trading companies brought imperial trading systems inland, while Indigenous peoples drew Europeans into their own patterns of trade and power. By the 19th century, the fur trade had covered most of the continent and the networks of business, alliances, and families, and the founding of new communities led to new peoples, including the Métis, who were descended from the mixing of European and Indigenous peoples. Trading territories, monopolies, and alliances with Indigenous peoples shaped how European concepts of statehood played out in the making of European-descended nation-states, and the development of treaties with Indigenous peoples. The fur trade flourished in northern climes until well into the 20th century, after which time economic development, resource exploitation, changes in fashion, and politics in North America and Europe limited its scope and scale. Many Indigenous people continue today to hunt and trap animals and have fought in courts for Indigenous rights to resources, land, and sovereignty.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.118
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1180.021

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 head0.069
GPT teacher head0.292
Teacher spread0.223 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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