CITY-FORMING ROLE OF THE UNIVERSITIES AND THE IDEA OF THE «UNIVERSITY QUARTER» IN SAMARA
Bibliographic record
Abstract
The article is devoted to the role of the university as a city-forming institution that produces cultural meanings that fill the physical space around the university. According to the authors of the article, universities can and should play an important role in the formation of a new type of city space. Samara case represents the group of educational leaders that have significant potential for actualizing the ideas of urban studies at least within one quarter. The article shows the city-forming impulse of universities of Kuibyshev/Samara since their appearance in the city during the revolutionary period, their strategic importance in wartime, and the colossal impact on the cultural life of the city and the humanitarian space of the Soviet urban intelligentsia of the 1960s, up to the modern process of “managerization” of universities, in connection with which the situation of searching for new forms of interaction between the university and the city is becoming increasingly essential. The authors propose the idea of creating a “University Quarter” in the central part of Samara and give some directions for the implementation of this brand in the socio-cultural dimension.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".