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Structural limits of single-barrier reform in algorithmic recourse: A formal series-system model with implications for digital health

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  • A C Demidont

Abstract

Algorithmic decision systems mediate access to healthcare, credit, employment and housing, yet individuals who experience adverse decisions face multi-stage barriers when seeking recourse. We formalize these barriers as a series-structured system with 11 empirically parameterized stages across three layers (data integration, data accuracy and institutional access) and prove that single-barrier interventions are bounded by baseline system success. Under baseline parameterization derived from federal datasets and peer-reviewed algorithmic audit studies, end-to-end recourse probability is 0.0018%. Removing any single barrier yields negligible improvement (

Suggested Citation

  • A C Demidont, 2026. "Structural limits of single-barrier reform in algorithmic recourse: A formal series-system model with implications for digital health," PLOS Digital Health, Public Library of Science, vol. 5(10), pages 1-13, October.
    • Handle: RePEc:plo:pdig00:0001784
    DOI: 10.1371/journal.pdig.0001784
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