Environment Design as a Method of Modeling a Cultural Space of a City
Bibliographic record
Abstract
The relevance of the studied problem because the study of the subject-spatial environment of the city, a comprehensive solution of which involves not only summing up the ideas of culturologists, architects, urban planners, designers, psychologists, anthropologists, sociologists, but also designing and modeling the artificially created environment as a process of forming the cultural space of the city. The content of the socio-cultural being of a human form the ideological and thematic basis of the designer's design plan. Modern environmental design, including an ethnic component, must correspond to the substantial and aesthetic characteristics of a particular regional culture. After the research work conducted by the authors of the cultural and artworks of scientists and specialists - designers, architects, we can argue that the design of the environment is a necessary component of the cultural image of the city. In this regard, there is a need for a comprehensive analysis of the factors of the formation of the cultural space, which becomes the basis for understanding the applied function of the designer’s activity, manifested in the decorative and ornamental nature of environment design objects. All components of the subject-spatial environment of the "Turkic-Tatar civilization" can be considered the basis of the design culture and as a result of the continuity of these traditions in modeling the cultural space of the city.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".