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Enregistrement W1579367082

Fur, Fortune, and Empire: The Epic History of the Fur Trade in America

2011· article· en· W1579367082 sur OpenAlexaboutno aff
Stephen Donnelly

Notice bibliographique

RevueHistorical journal of Massachusetts · 2011
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAmerican Environmental and Regional History
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFur tradeEmpireEPICValue (mathematics)HistoryFaithEconomic historyLawPolitical scienceAncient historyArtTheologyLiteraturePhilosophy
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Eric Jay Dolin. Fur, Fortune, and Empire: The Epic History of the Fur Trade in America. New York, NY: W. W. Norton & Company, July 12, 2010. 442 pages. $29.95 (cloth). Fur, Fortune, and Empire: The Epic History of the Fur Trade in America is a sweeping work that showcases the vital role the fur trade played in the colonization and expansion of the United States. Most of us think of Canada or perhaps the north woods of Maine or Minnesota when we think of furs. Few realize that the fur trade was a key factor in the survival of the Pilgrims and Puritans of Massachusetts, the Dutch in New York, and of the early settlers of the Mid-Atlantic States. The Puritans in particular were so assiduous in their pursuit of the fur trade that for a time all Europeans were referred to as Boston Men by their Native American trading partners. Eric Jay Dolin relates many of the familiar horrors and injustices of our relations with the native inhabitants, including the introduction of diseases, firearms, and alcohol. But he also sheds light on many little known facts that give a far more nuanced picture of the intercourse between two vastly different cultures. It is now taken as an article of faith that European settlers cheated the Native Americans out of vast wealth by trading trinkets for valuable furs. But iron fishhooks, pots, and tools were of immense value to members of a less developed culture, especially when all they needed to provide in exchange were pelts from a seemingly limitless supply. As for wampum and beads, they were a medium of exchange for the Native Americans of no less intrinsic value as gold was to the settlers, and therefore seemingly a bargain when traded for surplus pelts. This book demonstrates how the Native American culture grew to be dependent on European trading goods, and was transformed accordingly. The common perception of Native Americans living in harmony with nature before the advent of the White man was perhaps true. But it is also true that the near extermination of many North American fur bearing animals, with the exception of the buffalo, was accomplished primarily by these natives in pursuit of trade goods. The slaughter was initiated at the behest of the settlers to be sure, but it was perpetrated primarily by Native Americans. It was not until the widespread use of the leg hold trap allowed Western mountain men the option of easily killing their own prey that this equation started to substantially change. The author also recounts an anecdote that illustrates just how destructive alcohol, another item of trade, was to Native American cultures. Women learned from experience to hide all weapons of any kind from their men on the eve of a trading conference with the settlers. If the men received alcohol as compensation for furs, they would often drink until fighting broke out. This would frequently prove serious or fatal if weapons were at hand. Perhaps there is a history lesson here as our society debates open carry legislation allowing firearms into bars and restaurants. The early exploration of the West was primarily driven by the quest for furs. Gold, silver, and farmland were later factors that attracted succeeding waves of settlers to the West. But it was the beaver's misfortune that their pelts were perfect for the making of felt hats, then in high fashion in Europe, and they are what attracted the earliest inhabitants. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil0,095

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0050,004
Communication savante0,0040,005
Science ouverte0,0000,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,023
Tête enseignante GPT0,185
Écart entre enseignants0,161 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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