Preservation of the lost: The case of heritage in urban design of the “Ekaterinburg City”
Bibliographic record
Abstract
The research problem is the search for architectural, artistic and non-spatial methods that allow the integration of tangible and intangible heritage into the newly created urban fabric. A modern metropolis combines elements of both a holistic and homogeneous historical development, and elements of cultural heritage that need to be included in the modern urban planning, social and cultural context. The article gives a current approach to the preservation and adaptation of OKN in the urban environment. The goal is to present the “Ekaterinburg-CITY” case as an option for implementing mechanisms for preserving the values of the historical environment in a modern metropolis. Methods of monographic and comparative urban planning analysis, graphic reconstruction, and analysis of modern practices of protective urban regulation are used. The author examines the quarter of Yeltsin - Chelyuskintsev - October Revolution - Fighting Squads streets. This site is characterized by the maximum loss of the historical environment, but has signs of sociocultural value for Yekaterinburg. The algorithm for preserving values in conditions of maximum loss of objects of material culture is as follows: 1. Studying the history of the land plot (archival work, working with photographic documents, anthropological research - urban legends, etc.) in order to substantiate the set of values of the territory; 2. Building urban planning connections in order to design modern functional needs in the conditions of preserving historical objects. 3. Analysis of the historical and cultural significance of the land plot in order to form a list of intangible values - people and groups of people, professional or other associations that existed on the territory, etc. 4. Formulation of sociocultural meanings / codes of the territory in the conditions of a lost environment. 5. Selection of means of preserving identified values and meanings, taking into account all available options - for OKN: restoration, adaptation, citation, direct use, recreation; for modern solutions: interactive information technologies, gamification, etc. The improvement of "Ekaterinburg-CITY", taking into account the selected values and meanings, may include a balance of security zones and a modern approach to pedestrian traffic and meeting the needs of citizens, the use of natural paving, authentic coverings laid in historical ways or in a modern interpretation (gabions), the use of historical bricks with authentic hallmarks, creation of museum fragments (based on the work of Oleg Yalovoy) and the use of interactive technologies to present the history of the place (QR codes).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".