Spatial relations and perception of brownfields in old industrial region: case study of Svinov (Ostrava, Czech Republic)
Bibliographic record
Abstract
Regeneration of brownfields gradually becomes an important challenge for regional and local development across the East-Central European countries. Due to the recent huge economic transition and global societal changes thousands of abandoned sites (brownfields) sprang up across the landscape after various economic activities, the Czech Republic included. This paper evaluates the perception of brownfields along with their individual re-use options by local population in one of the city districts of Ostrava which was heavily influenced by industrialisation during the last 150 years (Svinov city district, city of Ostrava, eastern part of the Czech Republic). The first part of the paper is devoted to brief theoretical aspects of brownfields regeneration and its perception. The second part of the paper presents us with the results of the questionnaire survey which was carried out among local population of Svinov (n=163) focusing on the perception of five selected local brownfield sites. It was found out that the issue of brownfields rouses huge discussions among public of the model area of Svinov. Among the most supported re-use options of local brownfields greenery and cultural facilities were identified. Brownfield sites located outside the settled area of the city quarter are almost disregarded while the re-use of centrally located sites for greenery is strongly supported. In the final part of the paper, the findings are synthesized and recommendations for public administration and potential investors are formulated.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".