From Hubs to Deserts: Urban Cultural Accessibility Patterns with Explainable AI
This addresses spatial equity in cultural access for urban planners and policymakers, but it is incremental as it applies existing methods to new data.
The researchers tackled the problem of uneven access to cultural infrastructures in cities by developing a framework to measure spatial equity, revealing a core-periphery gradient where non-library cultural infrastructures cluster near urban cores and libraries provide broader coverage in denser, lower-income areas.
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.