Creative-based strategies in small and medium-sized cities: some European study cases
Bibliographic record
Abstract
During the last decades, creative and cultural approaches have been implemented in regional and urban development strategies as key drivers for competitiveness and growth. However, research literature tends to focus mainly in big cities and metropolis, not recognizing the potential of small cities in intermediate and rural regions in fostering territorial cohesion. Nevertheless, public policies based on creativity and innovation are being experienced in non-metropolitan and rural contexts around Europe, Canada and USA focused on economic revitalisation, urban regeneration and reversing de-population trends. These approaches are mainly based on historic precedents (‘path dependency'), in the exploitation of distinctive local attributes and assets regarding culture, environment, lifestyle and quality of life, besides specific investments in infrastructures or support programmes (such as incubators, live-work houses, and specific financing systems), which intend to induce the attraction of talent and the development of creative businesses. The main aim of this investigation is to examine the recent approaches to cultural and creative economy that are being implemented by small and medium-sized cities in Europe that still remain largely unstudied. The objective is to establish a typology of creative-based strategies through the analysis of the definitions adopted by regional and local authorities as well as the justifications and planning instruments used that reflect different priority goals or purposes. The paper engages the debate on rural and urban relationships as well as on the regional interdependencies. It is also stressed the demand for adapting widespread development policies to local specificities and to build up innovative forms of governance for a fully engagement of the local actors at different levels, in search of a competitive but also cohesive society. As a result, it is our intention to contribute to the theoretical thinking about the crucial factors for the sustainability of small local economies in regional development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".