Spatial planning and place branding: rethinking relations and synergies
Bibliographic record
Abstract
Spatial planning and place branding are allies in the discovery and creation of place narratives and assets as well as in contributing to spatial transformation or the improvement of the socio-spatial and spatial-economic conditions of a place. However, the existing and potential linkages between spatial planning and place branding are yet to be explored by both scientists and policy-makers. The objective of this paper is twofold. First, we reflect upon the central themes of this special issue by placing them in the context of larger debates on the position of place branding and spatial planning in society. Secondly, we show that this requires attention to the many ways in which planning and branding can cross-fertilize each other and to the embedding of both in evolving spatial governance structures. We then conclude with a typology expanding the understanding of this linkage between spatial planning and place branding.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".