Quantifying State Tort Liability in Public Service Failures Based on Real Administrative Performance Indicators

Abstract

Public service failures generate diverse forms of citizen harm, yet most legal systems still lack robust, data-driven methods for quantifying state tort liability. Existing frameworks often rely on qualitative assessments, fragmented reporting mechanisms, or retrospective inquiries that overlook measurable administrative performance indicators. This study develops an integrative analytical model that links real administrative performance datasets—such as service-delivery delays, unmet regulatory duties, inspection backlogs, and error rates in administrative decisions—with legally cognizable harms experienced by citizens. By synthesising recent advancements in accountability theory, empirical public management research, and contemporary tort-law scholarship, the article proposes a structured methodology for translating administrative underperformance into quantifiable liability outcomes. Drawing on established indicators used in modern governance systems, the study maps the causal pathways through which administrative malfunction escalates into compensable damages. It identifies three core liability-relevant dimensions: operational deficiency, systemic risk amplification, and individual harm manifestation. Using cross-sectoral datasets from public infrastructure, licensing, health-related administrative services, and regulatory agencies, the analysis demonstrates how variations in measurable performance indicators align with distinct categories of citizen loss, including financial burdens, service-access deprivation, and safety-related harms. The empirical component employs statistical correlations, threshold modelling, and harm-estimation benchmarks to illustrate how administrative metrics can be transformed into defensible quantitative evidence suitable for courts and oversight bodies. The findings indicate that incorporating performance indicators into tort-liability determinations enhances transparency, strengthens accountability, and reduces the discretionary bias that frequently characterises traditional legal assessment. The proposed model also facilitates earlier detection of administrative vulnerabilities, allowing governments to intervene before failures escalate into systemic harm. Ultimately, the study contributes a replicable framework capable of supporting judiciary actors, policymakers, and public administrators in constructing clearer, evidence-based evaluations of state responsibility. By grounding liability assessments in verifiable administrative data, the research moves the debate beyond normative critique toward a more measurable and operationalised understanding of public-sector accountability.

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