{"ID":2844706,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.07475","arxiv_id":"2511.07475","title":"From Hubs to Deserts: Urban Cultural Accessibility Patterns with Explainable AI","abstract":"Cultural infrastructures, such as libraries, museums, theaters, and galleries, support learning, civic life, health, and local economies, yet access is uneven across cities. We present a novel, scalable, and open-data framework to measure spatial equity in cultural access. We map cultural infrastructures and compute a metric called Cultural Infrastructure Accessibility Score (CIAS) using exponential distance decay at fine spatial resolution, then aggregate the score per capita and integrate socio-demographic indicators. Interpretable tree-ensemble models with SHapley Additive exPlanation (SHAP) are used to explain associations between accessibility, income, density, and tract-level racial/ethnic composition. Results show a pronounced core-periphery gradient, where non-library cultural infrastructures cluster near urban cores, while libraries track density and provide broader coverage. Non-library accessibility is modestly higher in higher-income tracts, and library accessibility is slightly higher in denser, lower-income areas.","short_abstract":"Cultural infrastructures, such as libraries, museums, theaters, and galleries, support learning, civic life, health, and local economies, yet access is uneven across cities. We present a novel, scalable, and open-data framework to measure spatial equity in cultural access. We map cultural infrastructures and compute a...","url_abs":"https://arxiv.org/abs/2511.07475","url_pdf":"https://arxiv.org/pdf/2511.07475v1","authors":"[\"Protik Bose Pranto\",\"Minhazul Islam\",\"Ripon Kumar Saha\",\"Abimelec Mercado Rivera\",\"Namig Abbasov\"]","published":"2025-11-08T19:35:53Z","proceeding":"cs.CY","tasks":"[\"cs.CY\",\"cs.LG\"]","methods":"[]","has_code":false}