Connecting an Urban Mosaic: Open Spaces and Sustainable Places of Belgrade
Bibliographic record
Abstract
Following a rapid transition to markets, democracy and private enterprise, Serbia’s capital Belgrade is emerging as a ‘global city’, but this ambition is coming at a cost to the environment and a loss of sense of place for its people. Diverse identities and changing values over time are being challenged as the city transitions out of a complex socialist past into a pervasively global economy, which by definition challenges locally embedded hybridity of place and puts strain on sustainable growth. Open spaces are required for city residents to live, work, and move efficiently, making the use, access, and ecological integrity of open spaces a city-wide priority. The dependence and attachment of city residents to these spaces provides an ideal baseline for analysis of different open space typologies integral to the urban fabric defining a wide range of urban resiliency strategies. This people-centered approach, coupled with an understanding of the contemporary and historical significance of open spaces, raises the question of how to improve and connect such forms to the urban fabric while respecting place identity in response to post-socialist spatial change. Our case studies inspect the socialist landscapes of public open spaces in New Belgrade as they have transformed in a contemporary context. Other case studies demonstrate the systematic loss of open space taken over by private informal housing on one hand, but also as people-driven initiatives reclaiming the urban landscape on the other. Using fresh empirical evidence and case study analysis at the neighborhood scale, this research employs an open space typology of resiliency in place for a connected urban mosaic of post-socialist Belgrade. The analytical framework draws on existing urban research in the context of post-socialist transition and advances a design matrix to analyze open space forms for connectivity in relation to place and sustainability.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".