Bibliographic record
Abstract
The intentions of this thesis are to explore potential combination of built intervention in historically and culturally significant urban areas focusing specifically on the waterfront of the Berlin Spree River and developing Queer spaces.The Spree River has historically served as a lifeline for Berlin.Its course has been a nexus for development, linking factories and railways, and fueling rapid growth and industrial expansion.Such expansion brought with it waves of immigration, together with the cultural enrichment and social tensions often associated with rapid industrialization and population growth.If such tensions are common in the urban realm, Berlin's social, economic, cultural, political, historical and environmental conditions demonstrate patterns of change and resistance that are uniquely charged.Queer spaces, such as the site of the Eisfabrik building are spaces of appropriation and empowerment.The ice factory is integrally embedded within the historic queer and music subcultures operating alongside the Spree River.Queer spaces were a vibrant component of urban life and public culture during the interwar period in Berlin, but were forced to adapt during the 1930s, camouflaging sites of resistance in opposition to the oppressive Nazi regime, which labeled suspected homosexuals with the pink triangle and carried out violent persecution of this group as a part of wider eugenic policies targeted at Jewish citizens.After the 1960s, Queer space evolved into a way to infiltrate a city and subvert heteronormative spaces for same gender sex.Since the 1990s, the "pink dollar" became an integral part of the music subculture and of municipal and corporate advertising strategies.Queer space was itself subverted, and turned into a highly visible marketing strategy, a way to promote nightlife to enrich the city.Each of these periods was characterized by different degrees of visibility and publicness, and by a variety of strategies for celebration and survival.This thesis focuses on and builds on an analysis the various historical uses and meanings of Queer space, building on these histories to invent new techniques of resistance, subversion, and transmission.These key terms were used as generative ideas to redesign several vacant Berlin sites within a larger urban strategy as a possible response to contemporary corporate waterfront redevelopment initiatives.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 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".