global cultural policy landscape

Description

This dataset accompanies the article "Decoding the Global Landscape of Cultural Policy: A Data-Driven Analysis Using Unsupervised Learning" (Park & Chang). It covers 179 nations (ISO 3166-1) and combines three types of variables used to derive an empirical typology of national cultural policy regimes via principal component analysis and K-means clustering. First, socioeconomic indicators: GDP per capita, PPP (World Bank, 2023); urban population share (World Bank, 2023); and the Human Development Index (UNDP, 2023 values). Second, cultural policy duration variables (author-collected): the historical depth of six categories of cultural and creative industry (CCI) legislation, measured as years since original enactment (2025 minus the year of first introduction, tracing amended laws back to their earliest predecessor) — framework/basic culture laws, content-industry laws, CCI tax incentives, CCI entrepreneurship support, copyright protection, and artist welfare systems. A value of zero indicates no such instrument exists. Data were collected through exploratory search restricted to credible official sources (government portals and international-organization databases); non-English legislative texts were translated with LLM assistance and verified against official summaries. Entries were audited for false zeros and anachronistic enactment years, and provenance records (law names and source URLs) are included. Third, CCI market indicators used for post-hoc analysis only, due to missingness: creative services exports and creative goods exports as shares of total trade, and entertainment & media market size per 1,000 population aged 15–69, from WIPO's Global Innovation Index 2025 (indicators 7.2.1, 7.2.4, 7.2.3). The deposit also includes the final cluster assignments (k = 2, 3, 4) and a Python replication script reproducing the PCA, clustering, statistical tests, and robustness analyses reported in the paper. Funding: Ministry of Education of the Republic of Korea / National Research Foundation of Korea (NRF-2025S1A5C2A02022476).

Institutions

• Sungkyunkwan University

  Seoul, Seoul

Categories

Funders

• Ministry of Education

  Government of the Republic of Korea

  Sejong-si, Sejong
• National Research Foundation of Korea

  Ministry of Science and ICT

  Daejeon, Daejeon

  Grant ID: NRF-2025S1A5C2A02022476

Licence