Traditions, Entrepreneurship, And Creative Governance: A Comparative Case Study of Cultural and Creative Industry and City’s Transformation in Macau and Tallinn
Bibliographic record
Abstract
Cultural and creative industry is important drive for the economy, especially in economic crisis and cities’ transformation, which have proven by some great cities like London, New York, Brussels, Toronto and etc. Thus, some governments of the world adopted these concepts to transform their cities expectantly by cultural and creative strategies or city plans, it has heightening the hot spot of cultural and creative industry in public, incubating creative entrepreneurs, and accordingly gradually changing the cities’ traditions where the culture and creative industry stemmed from. This paper selects two cities which are in transforming state with active governance to cultural and creative industry. They are Macau and Tallinn located in Asia and Europe respectively. This research explores the interactive effects of tradition, entrepreneurship, creative governance on evolving cultural and creative industry and transforming city. The paper adopts qualitative and quantitative methods together to collect the data such as governmental statistics analysis, participant observing, in-depth interviewing of different groups, and finally comparatively analyzed the first-hand data with constructive grounded theory. This paper focuses on the four major results. First, entrepreneurship of the city is the key drive for evolving culture and creative industry and transforming a city; second, the pattern of creative governance influences cultivating entrepreneurship for cultural and creative industry; Third, more importantly, transforming the city is closely related to the ability and model of the creative governance imposing on changing the traditions of the city;finally, cultural and creative industry is conducive to build creative milieu in specific area of the city and gradually change the dependence on traditional development path of the city.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".