Structuring the scattered literature on algorithmic profiling in the case of unemployment through a systematic literature review

Research output: Contribution to journalReviewpeer-review

Abstract

Purpose
This article examines the overlooked literature on algorithmic profiling in public employment services (APPES) in the field of public administration. More specifically, it aims to provide an overview and connections to identify directions for future research.

Design/methodology/approach
To understand the existing literature, this article conducts the first systematic literature review on APPES. Through inductive coding of the identified studies, the analysis identifies concepts and themes, and the relationships among them.

Findings
The literature review shows that APPES constitutes an emerging field of research encompassed by four strands and associated research disciplines. Further, the data analysis identifies 23 second-order themes, five dimensions and ten interrelationships, thus suggesting that the practices and effects of algorithmic profiling are multidimensional and dynamic.

Research limitations/implications
The findings demonstrate the importance of future research on APPES undertaking a holistic approach. Studying certain dimensions and interrelationships in isolation risks overlooking mutually vital aspects, resulting in findings of limited relevance. A holistic approach entails considering both the technical and social effects of APPES.

Originality/value
This literature review contributes by connecting the existing literature across different research approaches and disciplines.
Original languageEnglish
JournalInternational Journal of Sociology and Social Policy
Volume43
Issue number5/6
Pages (from-to)454-472
Number of pages19
ISSN0144-333X
DOIs
Publication statusPublished - 23 May 2023

Keywords

  • Algorithmic profiling
  • Artificial Intelligence
  • Public sector
  • Unemployment
  • systematic literature review

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