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All Journal Open Access Indonesia Journal of Social Sciences Open Access Indonesia Journal of Social Sciences
Urrashid, Harun
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Humanities Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Digital Visibility, Algorithmic Misclassification, and Welfare Exclusion Among Informal Workers: A Mixed-Methods Study in Indonesia Urrashid, Harun; Fitriyanti, Fitriyanti
Open Access Indonesia Journal of Social Sciences Vol. 9 No. 3 (2026): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher in collaboration with CMHC Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/oaijss.v9i3.325

Abstract

Background: Algorithmic governance is reshaping social protection, but the distributive consequences of automated welfare targeting in the Global South remain poorly understood. Objective: To examine whether digital transaction visibility and employment informality predict false-negative welfare exclusion, whether perceived algorithmic misclassification mediates these effects, and whether algorithmic procedural justice moderates them. Methods: An explanatory-sequential mixed-methods design combined an audit of 2,500 automated eligibility decisions, a cross-sectional survey of 640 household heads in Palembang, Indonesia, and phenomenological interviews with false-negative cases. Results: The audit found 72.3% accuracy and a 23.4% false-negative rate. Informality, misclassification, and digital visibility predicted exclusion, while procedural justice was protective; the model explained 52% of variance. Misclassification partially mediated the association, and non-digital informal workers had 4.27 times higher odds of exclusion. Conclusion: Algorithmic unfairness reflected parameterization bias against informal livelihoods, supporting conditional human oversight and accessible appeal mechanisms.
Digital Visibility, Algorithmic Misclassification, and Welfare Exclusion Among Informal Workers: A Mixed-Methods Study in Indonesia Urrashid, Harun; Fitriyanti, Fitriyanti
Open Access Indonesia Journal of Social Sciences Vol. 9 No. 3 (2026): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher in collaboration with CMHC Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/oaijss.v9i3.325

Abstract

Background: Algorithmic governance is reshaping social protection, but the distributive consequences of automated welfare targeting in the Global South remain poorly understood. Objective: To examine whether digital transaction visibility and employment informality predict false-negative welfare exclusion, whether perceived algorithmic misclassification mediates these effects, and whether algorithmic procedural justice moderates them. Methods: An explanatory-sequential mixed-methods design combined an audit of 2,500 automated eligibility decisions, a cross-sectional survey of 640 household heads in Palembang, Indonesia, and phenomenological interviews with false-negative cases. Results: The audit found 72.3% accuracy and a 23.4% false-negative rate. Informality, misclassification, and digital visibility predicted exclusion, while procedural justice was protective; the model explained 52% of variance. Misclassification partially mediated the association, and non-digital informal workers had 4.27 times higher odds of exclusion. Conclusion: Algorithmic unfairness reflected parameterization bias against informal livelihoods, supporting conditional human oversight and accessible appeal mechanisms.
Co-Authors Fitriyanti Fitriyanti