Renovation of residential areas for benefit of builders, state and citizens
Bibliographic record
Abstract
Abstract The paper deals with the problem of residential housing renovation projects for benefit of builders, citizens and state. The numerous interpretations of the “renovation” term we understand here as a complete renovation of the housing stock, i.e. demolition of old buildings and construction of new ones in contrast to their reconstruction and modernization. In other words, the renovation is considered as an urgent city-planning challenge involving changes in the field of territorial planning. On the example of the classic “Khrushchev” quarter of Irkutsk city, the authors propose a pilot renovation project with the distribution of roles and expenditures of all participants. The analysis conducted allows drawing a conclusion that renovation will be beneficial to the builder only if budget funds are invested in these projects in order to compensate the costs related to temporary resettlement of citizens from demolished dwellings. Another prerequisite is the governmental repurchase of apartments intended for resettlement of citizens from demolished housing at the prices not lower than those set by the authorities in the region. Citizens are ready to support renovation projects in case of their returning to their former place of residence in conditions improved from the point of view of the living environment comfort. To ensure the profit of the builder, the living area of the newly commissioned housing should exceed the area of the demolished housing by no less than one and a half times, provided that cheap technologies of modern prefabricated housing are used.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| 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".