Lennard Naumann

PhD Researcher
WZB Berlin Social Science Center
DYNAMICS Research Training Group

Git Google Scholar ORCID

Hi! I’m a researcher in the Institutions and Political Inequality unit at the WZB Berlin Social Science Center, and an affiliated member of the Research Training Group DYNAMICS.

My work focuses on prejudice and avoidance across ethnic and political divides: why people steer clear of those they see as different, and what this implies for how we live together as a society. To study this, I use experimental and observational methods for causal inference. In addition, I am interested in web scraping and the use of large language models in the social sciences.

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Publications

  • Intergroup Contact, Empathy Education, and Refugee-Native Integration in Lebanon (with Salma Mousa and Alex Scacco). The Economic Journal (forthc.).  [Preregistration]
    Intergroup contact interventions often yield limited results in deeply divided societies. We test contact and empathy education in Lebanon, where Syrian refugees comprise a quarter of the population. In a fully cross-randomised field experiment with 887 Lebanese and Syrian youth embedded in a psychosocial support programme, we find that contact has little effect on outgroup attitudes and behaviour, while empathy education consistently improves attitudes for Lebanese youth and behavioural engagement for both. The combined treatment achieves little beyond empathy alone, with no evidence of spillovers to parents (n = 595). In polarised settings, empathy education should precede — or replace — contact.
  • Power Law Distributions in Intrastate Conflict Intensity Dynamics (with Christoph Trinn). Conflict Management and Peace Science 40(4), 2023.
    The discovery of power laws in conflict intensities has spurred numerous explanation attempts. Two different interpretations have persisted: the notion that power laws are spurious results of random processes and the opposing view that power-law distributions attest to endogenous dynamics linked to self-organized criticality (SOC). We substantiate the SOC forest-fire model for intrastate conflicts, conceptualizing conflict potential as social pressure, measured by horizontal inequality. This potential is triggered by infinitesimal events. Their occurrence depends on the interaction density between conflict actors, operationalized as the conjunction of state capacity and non-state governance. In a global analysis of 143 conflict dyads, we find that 40 conform to a power law and 33 to a stretched exponential distribution, the two outcomes predicted by the model. We find evidence that the forest-fire model is a plausible approximation of the dynamics of intrastate conflicts, accounting for both the conformity and the non-conformity to power laws.
  • Attributing Agnostically Detected Large Reductions in Road CO2 Emissions to Policy Mixes (with Nicolas Koch, Felix Pretis, Nolan Ritter, and Moritz Schwarz). Nature Energy 7, 2022.
    Policymakers combine many different policy tools to achieve emission reductions. However, there remains substantial uncertainty around which mixes of policies are effective. This uncertainty stems from the predominant focus of ex post policy evaluation on isolating effects of single, known policies. Here we introduce an approach to identify effective policy interventions in the EU road transport sector by detecting treatment effects as structural breaks in CO2 emissions that can potentially occur in any country at any point in time from any number of a priori unknown policies. This search for ‘causes of effects’ within a statistical framework allows us to draw systematic inference on the effectiveness of policy mixes. We detect ten successful policy interventions that reduced emissions between 8% and 26%. The most successful policy mixes combine carbon or fuel taxes with green vehicle incentives and highlight that emissions reductions on a magnitude that matches the EU zero emission targets are possible.

Work in Progress

  • Chatting Across Divides: LLMs as Agents of Depolarization? Under review.  [Preregistration]
    Affective polarization, the animosity and avoidance between opposing partisans, is a concern for democratic societies. I test whether brief conversations with large language model chatbots implementing two established face-to-face narrative persuasion strategies reduce outpartisan animosity and avoidance. In a preregistered 2 x 2 factorial experiment with a quota-matched German online sample (N = 1,634; one-week follow-up N = 1,294), respondents discuss a polarizing issue with a perspective-getting (PG) chatbot, a moral-reframing (MR) chatbot, both, or neither. Compared to the pure control, the MR chatbot increases self-reported discussions with outpartisans in the following week (0.10 SD), and either chatbot increases sign-up for a future study involving discussions with human outpartisans (0.13–0.17 SD). The PG chatbot shifts policy attitudes toward the opposing side immediately after the conversation (0.09 SD), but the shift decays within a week. Neither chatbot changes outpartisan affect or avoidant preferences. Brief chatbot conversations can thus serve as a scalable first step toward cross-partisan contact, even when feelings toward the other side remain unchanged.
  • Outgroup Avoidance in Online Dating: Evidence from a Field Experiment.  [Preregistration]
    Recent meta-analyses suggest that, while contact can reduce prejudice, the effects are small, particularly in well-powered field experimental studies with delayed outcome measurement. One reason intergroup contact may fail to produce larger effect sizes is that those prone to avoiding outgroup contact are less likely to benefit from or engage in such encounters. However, research into the drivers of intergroup avoidance is scarce. In this study, I systematically investigate the patterns and drivers of intergroup avoidance in an online dating context. In partnership with a large European online dating platform, I first analyse user data to examine the extent and covariates of ethnic bias in swiping behavior. Next, I conduct a large-scale field RCT in which users are randomly assigned to one of three brief video treatments. They delivered on the platform and designed to test three psychological mechanisms that potentially drive intergroup avoidance: ingroup norms, outgroup norms, and perceived group commonality. Behavioral swiping data is complemented by an endline survey including measures of intergroup contact preference, intent, and behavior.
  • Political Connections: Measuring Political and Business Elite Networks (with Lisa Garbe, Yuequan Guo, and Macartan Humphreys).
    Elite connections shape political and economic outcomes but are difficult to measure. Traditional methods rely on surveys or shared affiliations, which lack scalability and clear interpretation. We propose a scalable, interpretable approach to map elite networks by compiling elite lists, detecting co-appearances in media, coding interactions with large language models (LLMs), and constructing network ties. This complements conventional methods and suits dynamic elite politics. Applied to Germany (2013–2023), our data includes 750 parliamentarians and 1,051 top executives. We collected 42,366 articles from 30 newspapers, identifying co-appearances. Open-source LLMs code interactions such as meetings or conversations, enabling nuanced network definitions. We validate networks qualitatively and quantitatively by linking them to events like elections and comparing them with education-based networks. This method expands elite network research beyond typical scopes, offering scalable, interpretable insights into how political and economic elites connect and influence each other.
  • “Native Flight” in Urban School Districts? Evidence from Primary School Registration Data in Berlin (with Bernd Beber, Moritz Matzner, and Macartan Humphreys).
    We investigate parental school choice in Berlin, Germany. Anecdotal evidence suggests that nonmigrant “natives” take steps to avoid or seek out catchment area schools due to the ethnic composition of student bodies. Indeed, school segregation has been documented across Europe, but the lack of high-resolution data on school choice and migrant populations has made it difficult to precisely show the extent to which schools are more (or less) segregated than we would expect given catchment area demographics and to analyze the process that leads to such segregation. We contribute to this debate with an analysis of a never-before-used dataset of 35,000 school choice forms that parents must complete to enroll their child in elementary school. We combine this data with a newly compiled set of administrative data covering Berlin’s several hundred elementary school enrollment zones for the years 2000 to 2018, which includes demographic and socioeconomic zone characteristics, student population indicators, and various school attributes and performance metrics. We explore in particular the extent to which we see Schelling sorting, where even weak preferences for separation from another group (and small changes in zone composition) can dynamically spiral to produce extreme patterns of segregation, and we develop policy implications for how to counteract such dynamics.

Policy and Outreach

  • Towards Genuine Collaboration in International Research (with Nora Chirikure). WZB Mitteilungen 184, 2024.
    Researchers worldwide continue to face significantly unequal starting opportunities, particularly in terms of research funding, academic career paths, visas, and networking. Nora Chirikure and Lennard Naumann explore what is needed to establish truly equitable South-North research partnerships and to ensure the success of research originating from the Global South.