Beyond the Accreditation Cut-off: A Decision-Aiding Framework for Risk-Proportionate Higher Education Regulation
DOI:
https://doi.org/10.1590/SciELOPreprints.17560Keywords:
accreditation, angola, higher education quality assurance, meta-evaluation, thresholds, multicriteria decision aiding, risk-proportionate regulationResumen
Purpose — This article develops a decision-aiding framework for risk-proportionate higher education regulation, using national external assessment and accreditation (EAA) results for 877 undergraduate programs in Angola. It examines the information lost when a multidimensional assessment is reduced to a binary accreditation decision and asks how distance from the legal cut-off can support proportionate supervision without creating a second accreditation scale. Design/methodology/approach — The legal cut-off remains fixed at 60.00%. A signed regulatory deficit, R = 60 − S, distinguishes shortfalls from surpluses. The framework combines official performance bands, provisional supervision zones, illustrative indifference and preference thresholds, mandatory-indicator safeguards, contextual review, sensitivity analysis, and exploratory K-means profiles. The proposed thresholds are normative decision-support parameters rather than empirically estimated cut-points and therefore require calibration and validation. Findings — The mean score is 56.94%, the median is 60.33%, and 475 of 481 accredited programs (98.75%) are concentrated in level C. Companion multilevel evidence reports a null-model ICC of 0.512, indicating substantial between-HEI variance without identifying its causal mechanisms. These empirical results establish concentration around the legal threshold and heterogeneity within formal accreditation categories; they do not validate the proposed supervisory thresholds. Originality/value — The article separates legal accreditation status from analytical supervisory intensity and explicitly distinguishes between empirical evidence and normative decision parameters. Its contribution is a transferable decision architecture in which distance to the cut-off, mandatory dimensions, contextual evidence, institutional dependence, sensitivity analysis, and human review inform regulatory follow-up while preserving the legal accreditation rule
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Derechos de autor 2026 Amaro Segunda Ricardo

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
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