Research & Writing
My research centres on the comparative politics of citizen-state interactions.
Civic actions and political attitudes
I investigate how the state compels, engages, and responds to citizens, and the attitudinal and behavioural consequences of these encounters.
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Voting as Social Categorisation
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Local Institutions, Participation, and Trust
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How does compulsory civic engagement shape citizens' attitudes? While voluntary participation has received extensive scholarly attention, the effects of mandatory civic duties remain understudied. This paper examines compulsory civil service in Vorarlberg, Austria, where citizens in rural municipalities must perform compulsory manual labour or pay substitute taxes. First, I triangulate evidence from several administrative sources to identify the towns that still enforce the service and to identify predictors of service adoption. I find that enforcement of compulsory civil service is associated with higher altitude, smaller population size, and stronger civic infrastructure (as proxied by fire brigade membership density and electoral turnout). Second, using a mixed-methods approach combining in-depth interviews with an original field experiment, I investigate how mandatory civic engagement affects institutional trust and political attitudes. Preliminary interviews with local officials reveal that service uptake is undermined by informational and registration barriers. To address these barriers and identify causal effects, I employ a quasi-experimental design leveraging information provision as an instrument for service uptake. I then estimate the effect of actual participation on trust and attitudes. I hypothesise that reducing information and registration barriers increases service uptake, and that compulsory service will enhance trust in local institutions through direct engagement and visible community benefits, while undermining trust in national and supranational institutions. This study contributes to understanding how mandatory civic engagement and participatory interventions shape political attitudes and whether such programmes strengthen or undermine democratic legitimacy.
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Politics in Human Time: Institutional Democracy and Lived Democratic Experience (with Christopher J. Anderson and Damien Bol)
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Democracy is organized through political institutions and encountered across citizens’ lives. Political systems and populations therefore carry democratic history forward differently: institutions change with political events, while the experience embodied in living populations generally evolves more gradually. The population carrying that experience is itself continually renewed as generations succeed one another across countries with different demographic structures, changing whose political histories compose the demos. We introduce the concept of Lived Democratic Experience (LDE) to make this population-level history observable. Combining records of democratic rule with fine-grained demographic data, we measure the number of years citizens have lived under democracy and the average share of their lives it has occupied. Our analyses reveal substantial cross-national variation and show that democratic experience remains surprisingly limited across much of the world. LDE is strongly related to contemporary institutional democracy but diverges from it where democratic institutions are recent, interrupted, or weakening. LDE is therefore not simply an alternative measure of contemporary institutions, but captures democratic history embodied in living citizens. Distinguishing institutional time from human time reveals the different population histories within which democracy is established, reproduced, weakened, and potentially recovered.
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AI and political decision-making
I study how artificial intelligence reshapes the interactions between citizens and the state. My research looks into persuasion, autonomy, and accountability.
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The Autonomy Paradox: Artificial Intelligence and the Foundations of Political Behavior
(with Christopher J. Anderson), forthcoming in Perspectives on Politics
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Decades of research in political behavior show that citizens struggle with information, rely on cognitive shortcuts, and face barriers to participation. They are increasingly using AI tools to make sense of political information and express views, while interacting with platform curation systems that shape how views circulate through democratic politics. Although these tools appear suited to address the limits of democratic citizenship, they do more than transmit content. They help interpret information, articulate views, and affect what is prioritized, seen, and circulated. In doing so, these systems shape the formation of political judgments and citizens’ capacity to translate them into action. As a result, they can reduce barriers to participation while weakening the independence of political judgment, or they can support reflective preference formation while constraining citizens’ ability to act on those preferences effectively. We call this tension the autonomy paradox. To make sense of it, we focus on how citizens engage with AI systems in ways that affect belief formation and political action. We develop a framework and research agenda for identifying when AI supports autonomous citizenship, when it substitutes for citizens’ judgment or agency, and why the same systems produce different outcomes across political tasks depending on how citizens use them.
- Media: EUobserver
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- AI in citizen-representative interactions (with Christopher J. Anderson, Miguel M. Pereira, and Julia Schulte-Cloos)
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Artificial Intelligence, Personalised Persuasion, and Climate Attitudes
(with António Valentim)
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Can interactions with AI change climate opinion? Combating climate change requires citizens to recognise its urgency, make sustainable choices, and advocate systemic changes. As AI becomes more prevalent, we test the extent to which its use can change climate opinions and policy preferences. We argue that AI – particularly personalized content – could influence climate attitudes and overcome limitations of pure information provision. In this pre-analysis plan, we hypothesize that engaging with large language models (LLMs) can shift public attitudes towards climate change by delivering tailored messages at scale. We will conduct a survey experiment in the UK to examine how dialogues with an LLM affect respondents' climate opinions and policy preferences. These dialogues will leverage previously collected individual-level information to tailor interactions. We will compare effects of personalized interactions about climate change with those of interactions on different topics, non-personalized climate interactions, and standard informational statements. Overall, our study contributes to research on climate opinion and consequences of AI for politics.
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