Welfare experiments as tools for evidence-based policy making? The political debate on Twitter about the basic income trial in Finland. (4th July 2022)

• Record Type: Journal Article
• Authors: Parth, Anne-Marie; Nyby, Josefine
• Is Part Of: Policy studies. Volume 43:Number 4(2022)
• Page Start: 772
• Page End: 790
• Publication Date: 2022-07-04
• Subjects: Policy experiments -- evidence-based policy making -- basic income -- Finland -- Twitter -- framing -- social media debate; Policy sciences -- Periodicals; Great Britain -- Economic policy -- Decision making -- Periodicals; Great Britain -- Politics and government -- 1945- -- Decision making -- Periodicals; 320.605
• DOI: 10.1080/01442872.2020.1772217
• Languages: English
• ISSNs: 0144-2872

Abstract

ABSTRACT: Considered scientific and objective tools, welfare experiments have become increasingly attractive for testing innovative policy reforms. The basic income especially has been a popular policy experiment, trialed in several communities. However, do policymakers use welfare experiments as a policy instrument to gain empirical evidence for contested policy ideas? What can the political debate on Twitter reveal about the strategic functions of welfare experiments? Using a unique dataset of Finnish MPs' Twitter tweets on the basic income trial in Finland from 2017 to 2018, this article finds that Members of Parliament (MPs) neither waited for new empirical findings nor argued in a constantly coherent way. In contrast, while waiting for the evaluation, the tweets of the MPs became increasingly negative, even though no further empirical knowledge was available. The quantitative empirical analysis concludes that the reference to core welfare paradigms was essential to the legitimisation of basic income, although framing between political parties differed. In summary, this article contributes to a better understanding of the strategic function of welfare experiments and demonstrates the usefulness of Twitter data for social policy analysis that goes beyond hashtag-based, big data-driven research.