Ruts of Gentrification: Breaking the Surface of Vienna's Changing Cityscape
Bibliographic record
Abstract
Last year, the city of Vienna celebrated the 150-year anniversary of the opening of the Ringstrasse, the central ring road that stands as symbol of the huge structural renewal that accompanied the transformation of the Habsburg empire’s capital into a rapidly growing modern city. The anniversary acquired poignancy on account of the way Vienna’s population is once again growing rapidly, with an estimated ¼ million people to be added to the city’s population over the next decade. While accommodating urban migrants was not a priority in Ringstrasse Vienna, and working class districts are not part of iconic mapped mediations, the current city council, a coalition of Social Democrats and the Green Party, studiously tries to avoid 19th-century urban modernity’s “mistakes” in their efforts to accommodate the growing population, and they let the Viennese, and the world, know. This time, GIS and digital mapping are mobilized for planning, mediating and communicating large-scale development and renewal projects. This paper looks at the mediations of three crucial sites of contemporary urban transformation in Vienna that mobilize the affordances of new technologies: “Loftcity,” a loft development cum cultural centre on the site of one of Vienna’s largest factories, the Ankerbrotfabrik; the transformation of the district surrounding Vienna’s new Hauptbahnhof; and Aspern, “Vienna’s Urban Lakeside,” a new satellite town promoted as a city of the future. By comparing the historical traces that remain in the mediations of these sites with their 19th-century counterparts, a geocritical reading of Vienna’s gentrification emerges that situates spatial practices in historically grown lines of connectivity, presaging and transcending traditional forms of classification, such as national divides or urban/suburban dichotomies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".