Currie, Morgan (2024). Metadata for Automating Universal Credit, 2022-2023. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-857018
In the UK, the Department for Work and Pensions (DWP) uses automated systems for Universal Credit (UC), the country's largest social security payment, to determine eligibility, calculate monthly benefits and detect fraud. Unique to UC, automation determines monthly pay based on a complex set of means-testing variables and data linkages with other departments. What are the policy rationales behind UC’s system? How do claimants experience the monthly means-tested payment? And how does the system shape the way DWP carries out its welfare policies? This project contributes to our understandings of digital welfare broadly, exploring how claimants experience these systems and can inform their technical design.
Data description (abstract)
Automating Universal Credit studies the automated and digital aspects of Universal Credit (UC), a social security benefit in the UK. Recipients mainly interact with UC staff through an online account, and their monthly entitlement is calculated by an automated, means-testing system that factors their personal circumstances and monthly income if they work. The study used qualitative longitudinal methods, which allowed us to understand how UC claimants experience UC in near real-time, including the systems' unexpected behaviours and errors. The study has achieved two main high-level findings. First, we found that Universal Credit creates temporal mandates by applying a fixed, monthly assessment period of earnings for working claimants. We developed the concept of temporal punitiveness to describe how this monthly period creates problems for claimants who are paid their wages on a weekly/bi-weekly basis; due to the rules of calculation within the system, this misalignment may lead to the loss of entitlement. Likewise, parents have a very narrow timeframe to submit for childcare reimbursement; if parents do not submit within certain parameters, they may not be reimbursed. Second, we argue that administrative burdens may originate at the technical layer that citizens interact with to receive a service. To evidence this argument, we identify how the mechanism for reporting earnings data to UC creates administrative burdens for working UC claimants: we found that several claimants' earnings data reported to UC for the automatic calculation was wrong and thus, claimants needed to start a dispute process with the DWP. A FOI request we submitted to the DWP revealed that this happens to 5-6% of claimants each year. UC’s automated tools function at times as gatekeepers to social security entitlements, raising concerns about the current design of UC as a form of social security.
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Sponsors: | Economic and Social Research Council | |||||||||
Grant reference: | ES/V016709/1 | |||||||||
Topic classification: |
Social welfare policy and systems Science and technology |
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Keywords: | SOCIAL SECURITY BENEFITS, AUTOMATION, SOCIAL WELFARE ADMINISTRATION, SCOTLAND, UNITED KINGDOM, GOVERNMENT DEPARTMENTS, WELFARE POLICY, DATA | |||||||||
Project title: | Automating Social Security in the UK: A Study on Incorporating Claimant Voices in the Design of Universal Credit | |||||||||
Grant holders: | Morgan Currie | |||||||||
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Date published: | 21 Mar 2024 17:06 | |||||||||
Last modified: | 21 Mar 2024 17:07 | |||||||||