Does German Cultural Studies need the Nation‐State Model?
Bibliographic record
Abstract
the nation-state model has long been the basis for the institutional structure in place to teach languages, literatures, and culture at american universities and elsewhere. Nationalism was in fact formative for the establishment of the discipline of German literary and cultural studies itself-and not something brought into its disciplinary history from the outside, as Jakob Norberg, building on earlier research (see for instance Costabile-heming/halverson; hohendahl, German Studies; Denham/kacandes/Petropoulos, and McCarthy/Schneider), in a recent issue of the German Quarterly has shown ("German literary Studies and the Nation. " GQ 91.1, 2018, pp. 1-17). over the past few decades, this history linking our profession to the nation-state model has often been questioned by those teaching German literature and culture, while the status of German in general was institutionally quite secure and there was little reason to think about structural changes. this, however, has changed. Not only do fewer students in the United States and across the globe opt to major in German; administrators at many institutions increasingly prefer language, literature, and culture departments to be part of larger structures, thus (implicitly or explicitly) also questioning the value of the nation-state model that so long has been part of our disciplinary history. in addition, scholars themselves in their teaching and research increasingly choose to emphasize the many global contexts of German literature and culture as meaningful for the study of German itself.
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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 | 0.024 | 0.107 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".