Writing the Asphalt Jungle: Berlin and the Performance of Classical Modernity 1900–33
Bibliographic record
Abstract
In this paper I explore the textual performance of Berlin in the early 20th century, focusing on the multiple spaces of classical German modernity (1900–33) as they are described and reinvented within the poetics of a rapidly modernizing metropolis. It is argued that writing Berlin cannot offer a unifying text or conceptual system which arranges the city ipso facto into a single territory, a generalise space of selected indices and icons. Alternatively, the writing of the city explores the ongoing transformation of the city in text. My purpose in this paper is, therefore, irrefutably bound up with the capacity of the urban text to remap imaginatively the changing condition of the city onto the text itself—hence the fashioning of textual presences as surrogate city spaces. The notion of performance is furthermore deployed to account for the immediacy and evanescence characterizing the Berlin of classical modernity, a period that rehearsed the contradictions of modernization in accelerated form. From journalistic reportage to novels, the textual performance of Berlin necessitates an enabling reception and adaptation to the destabilizing nature of urban industrial modernity, which in turn can be plotted in two interrelated ways: first, in the proliferation of textual strategies which approximate the montage effect of the incipient modernization of the city; second, in the writerly anticipation of cinematic innovations as the scripting of a ‘moving’ urban culture of modernity. Taken together, these writings inhabit traveling geographies which provide models of performative identification for appropriating and embracing the complexity of the modern city.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".