Bibliographic record
Abstract
The "margins" in Petra Fachinger's work are occupied largely by second-generation migrant writers from Spain, Italy, and Turkey, German Jewish writers of diverse ethnic origins, and writers born in the GDR. She demonstrates that during the 1980s and 1990s writers from various cultural backgrounds engaged in oppositional discourse to construct their own version of Germany and write back to the German canon. While most studies of texts by minority writers in Germany favour content over form, Fachinger focuses on identifying counter-discursive strategies, and applies postcolonial theory concerned with textual resistance to the German situation. In doing so, this study effectively relates marginal writing in Germany to similar forms of writing in other national and cultural contexts. The oppositional impulse, whether manifested in counter-canonical discourse, postcolonial picaresque, hybridity, rewriting of genre, or grotesque realism, is prompted by the exclusionary politics of the dominant culture. The discursive strategies used by the authors discussed to rewrite Germany expose the assumptions that underlie German public discourse and destabilize notions of Germanness, Jewishness, and Turkishness. Fachinger's reading of texts by marginal writers in Germany, all of whom endeavour to resist marginalization while simultaneously experiencing or even celebrating the margin as a site of empowerment, was motivated by the absence of comparative studies of such writing. Rewriting Germany from the Margins demonstrates the necessity and usefulness of comparative approaches to minority discourses across national and cultural borders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".