Replication data and code: Scale Invariance and Symmetry-Breaking Predictor Selection in Modeling the Accreditation Status of Chilean Universities from Financial and Management Indicators

Institution-year panel (48 Chilean universities, 2017-2021; outcome = years of institutional accreditation) and self-contained Python code reproducing the analysis reported in the article submitted to the Symmetry (MDPI) Special Issue ‘Symmetry in Uncertainty and Intelligent Decision-Making’: baseline OLS, ordered logit, cluster-robust standard errors by institution, Ridge with institution-level bootstrap, leave-one-institution-out cross-validation, and CRUCH-by-predictor interaction tests for symmetry breaking. Indicators are public (Chilean Higher Education Information Service, SIES), harmonized by the authors. With a fixed seed the bootstrap is reproducible.