The Diminished Importance of Cultural Sustainability in Spatial Planning: The Case of Slovenia
Bibliographic record
Abstract
Formal spatial planning procedures tend to neglect the importance of socio-cultural elements that are inherently present as part of 'soft infrastructure' and are constituted from traditions, lifestyles, wishes, and the routines of individuals that form a local community. In contrast, the concept of cultural sustainability is closely linked with the socio-cultural heterogeneity of a local community. The inability of the formal spatial planning system in Slovenia to adequately engage with the social wishes and resistances of residents is highlighted in situations involving problematic confrontations between the members of the dominant 'common culture' and marginal groups. Two cases from Ljubljana are presented: the stigmatization of the Fužine neighbourhood and the problematic of mosque construction. The cases illustrate that the 'majority' of residents tend to perceive many subcultural representations in space as foreign, non-indigenous elements that could disrupt the everyday routine in a local community. They show how the deficiencies of the current spatial planning system in Slovenia are unable to address challenges posed by contemporary society's cultural, social, and economic transformations and can work quite the opposite way – by increasing the complexity (and level of difficulty) for possible implementation of measures supporting cultural heterogeneity in planning practice.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".