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Enregistrement W4361859564 · doi:10.1162/jinh_r_01921

<i>Immigration: An American History</i> by Carl J. Bon Tempo and Hasia R. Diner

2023· article· en· W4361859564 sur OpenAlex

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Notice bibliographique

RevueThe Journal of Interdisciplinary History · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueRace, History, and American Society
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmigrationHistoriographyRacismImmigration lawState (computer science)HistoryBureaucracyGender studiesImmigration policyPolitical scienceSociologyGenealogyLawPolitics

Résumé

récupéré en direct d'OpenAlex

In this book, Bon Tempo and Diner provide a readable and expansive survey of U.S. immigration history. Moving briskly from the seventeenth century to the present day, they chart the twists and turns in U.S. immigration patterns, policies, and bureaucracies, as well as in the lives of U.S. immigrants. Along the way, they incorporate many recent, important trends in immigration historiography—including an emphasis on race and racism, on immigrants from all over the world (both women and men), and on its transnational dimensions (notwithstanding the subtitle “American History”). They also dot their narrative with compelling personal stories of varied, lesser-known immigrants—Irish union leader Leonora Barry; Sudanese refugee Achut Deng; Louise Norton, Malcolm X’s mother, who migrated to the United States from the West Indies by way of Canada; and struggling Chinese artist Qiming Lui.In a book of such breadth, central arguments can be difficult to decipher, but Bon Tempo and Diner stress two of them. The first is the “primary significance [of] … economic matters”—especially “work and the nation’s labor needs”—“in explaining the United States’ immigration history” (4). The second is the centrality of the state in determining which immigrants could come to the United States, which of them could stay, which of them could become full-fledged members of the nation, and which of them could access a full range of rights, protections, and resources in their new home. In concluding, the authors highlight three surprisingly straightforward historical themes that “best arm our readers as the story of immigration and the United States continues to unfold” (362). In addition to the argument above about the state’s importance, they insist that “immigrants came to North America in search of a better life” and that they “are like us” (362, 363).In making these and other claims, Bon Tempo and Diner draw from a mix of sources, including government and think-tank reports, newspaper and magazine articles, memoirs, oral histories, and even an occasional YouTube video, campaign advertisement, or protest poster. But their main source is the scholarship of historians and, to a lesser extent, political scientists, sociologists, economists, legal scholars, anthropologists, and others. Hence, the book has a faint interdisciplinary flavor. Its main audience, however, appears to be non-specialists in immigration history, as fine an audience as any but one that brings some disadvantages, especially for readers of this journal. In their understandable effort to keep the story moving, Bon Tempo and Diner tend to shy away from any deep engagement with the big theoretical debates that roil much of the immigration scholarship. For example, they avoid any analysis of the extent to which political institutions, political traditions, social forces, economic interests, cultural dynamics, or some combination thereof is responsible for the many shifts in U.S. immigration policy over time. Nor do they interrogate the role that capitalism, in its various configurations, played. Is it true, as one scholar recently suggested, that the “interests and strategies of capital” have largely determined U.S. immigration policy over the years?1 For a book that places “economic matters” at the center of the story, it is surprising that the authors seldom address these issues systematically.Immigration is nonetheless a valuable, far-reaching history. Those wishing for more interdisciplinarity and theory, however, might consult older overviews by Ngai, Tichenor, and Zolberg.2

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,078
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,003
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,019
Tête enseignante GPT0,299
Écart entre enseignants0,280 · 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