Border crossings: The making of German identities in the New World, 1850-1914.
Bibliographic record
Abstract
Border crossings, in both their literal and figurative sense, are central to the experience of migration. This study explores the making of German identities in two localities, Berlin (Ontario) and Buffalo (New York) in the decades between 1850 and 1914. It is interested less in the construction of ethnic boundaries, and, more so, in the social acts of exchange across them. It argues that out of the conversation between 'German', 'Canadian', and 'American' identities a German public emerged. This public was a malleable entity. At times, its boundaries stretched as far as Germany itself. It also spanned Canada and the United States; for German language, culture, and festivity provided common ground for migrants on both sides of the border. Then, again, the German public seemed to splinter in two, with public conversations on German-ness acquiring a distinct Canadian or American tinge. Although the German public bore a remarkable similarity in both Buffalo and Berlin, grounded as it was in a shared festive culture, the national sphere left its indelible print. The discourse of ethnic contributions that loomed so large in the United States never crossed the border into Canada. In Berlin, ethnic leaders instead sought to de-politicize German culture and to reinforce the idea of dual loyalties. In both countries, the idea of race minimized the distance between 'Anglo-Saxons' and 'Teutons'. Yet in reconciling competing national mythologies, German Canadians highlighted the perceived closeness of the German and British Empires, whereas German Americans deftly appropriated the notion of cultural superiority. While its contours were sketched by ethnic leaders, the German public was, by no means, a unified entity. To capture its motion and fluidity, and to minimize a dependence on cultural gatekeepers, this study turns to the colourful history of the singers' festivals (Sangerfeste)---public celebrations of German music, language, and culture---and seeks to unravel the webs of meaning and experience spun around the history of German-language schooling. In so doing, it finds that, by the early twentieth century, the culture of consumption began to rival German festive culture, while the German mother tongue was refashioned into a language of modernity. The German public, in short, had transformed from a means of communication into a symbol of ethnic identity. (Abstract shortened by UMI.)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".