NORMATIVE APPROACHES IN MAKING CULTURAL QUARTERS AND ASSESSMENT OF CREATIVE INDUSTRY PARKS IN SHANGHAI
Bibliographic record
Abstract
This article aims to synthesize the principles of making cultural quarters in literature and test their applicability in creative industry parks in the Chinese context. Extant literature on creative industry parks in China lacks an evaluation instrument for evaluating the performance of creative industry parks. This research reviews normative theories regarding cultural quarter making and identifies three approaches, namely the area-based approach in cultural quarter design, architectural design principles (tailored to cultural quarters), and a comprehensive framework that comprises three dimensions, i.e., activity, built form, and meaning. These normative approaches were applied to evaluate the quality of creative industry parks that emerged in Shanghai in the recent decade. Qualitative research methods, including on-site reconnaissance, observation, and interview, were adopted. The former two approaches revealed good design practices in Shanghai’s creative industry parks. A systematic evaluation of the said parks through a comparative study suggests significant disparity in the dimensions of architectural design and place making. Additionally, indicators of state support for micro and small creative industry companies and arts funding are less applicable in Shanghai. These findings reveal the role of the private sector in constructing a diversified creative environment which was previously enshrined by the state. With these outcomes, this research partially endorses the value of the normative theories to guide the practice of making and evaluating cultural quarters in the Chinese context.
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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 | 0.020 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".