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The Research Priority Area, Emergent Phenomena in Society: Polarisation, Segregation and Inequality (RPA PSI) is an interdisciplinary collaboration at the University of Amsterdam with the goal of uncovering the interplay between the various mechanisms underlying the social phenomena of polarization, segregation and inequality combining fundamental research and societal-driven (non-academic) research. The collaboration involves various faculties at the University of Amsterdam, including the Faculty of Science (FNWI), the Faculty of Economics and Business (FEB), the Faculty of Social and Behavioral Sciences (FMG) and the Faculty of Law (FdR) as well as the the knowledge institute Statistics Netherlands (CBS). 

The study of Polarization, Segregation and Inequality (PSI) is typically conducted in isolation by different research groups using a variety of methodologies. Yet, it has become increasingly clear that these three phenomena are inextricably linked via a web of causal mechanisms, including the effects of policy and law, operating at different temporal and spatial scales. Uncovering such a network is the main goal of this RPA and requires an interdisciplinary approach that brings together strong academically driven research initiatives at the UvA as well as societally driven research at the CBS into a coherent effort. The RPA PSI programme builds upon on a solid foundation of various initiatives and research groups. These include the
Dutch Institute for Emergent Phenomena (DIEP), which is now leading the focus area Foundations and Applications of Emergence (FAEME) at FNWI, aiming to understand emergent behavior over the next five years (Armas, de Boer, Mandjes, Mulatier); the focus area Polarization: an interdisciplinary multi-level approach (PIMA) established at FMG which aims to unify views on polarization in the social/behavioral sciences (van der Maas, Uitermark); the recently awarded ERC Advanced Grant Beyond the tipping point (BTP): cascading transitions in the behavioral/social sciences (van der Maas); the ongoing project on school segregation (COMPASS) funded by the Amsterdam Municipality (Lees); the NETWORKS gravitation programme (Mandjes); the Center for Nonlinear Dynamics in Economics and Finance (CeNDEF) at FEB (Diks, Tuinstra); and The Amsterdam Centre for Transformative Private Law (ACT) at FdR (Mak).

RPA PSI aims at a new integrated understanding of these three social phenomena by modelling insights and data from the social and economic sciences using frameworks based on statistical physics and computational sciences. The main goal of this RPA is the development of a mathematical and computational toolbox suitable for, but not limited to, the study of PSI, as well as a computational model of an artificial society exhibiting PSI that can be constrained with available data from the CBS, the municipality of Amsterdam and other sources. This model will be used to test and design interventions aimed at reducing current levels of PSI. We expect that the engagement with policy makers on this topic via the
POLDER Simulation Centre led by the Institute for Advanced Study at the University of Amsterdam, can support an evidence-based policy making process.

The fundamental understanding of the network of causal relationships between the three emergent phenomena (PSI) will be used to develop a monitoring tool that can serve as an indicator of critical levels of societal disintegration, with potentially high societal impact. More generally, we expect that the deeper understanding of PSI gained through this coordinated research effort will improve the social impact of policies, legislation and interventions and potentially lead to a more equal and fair society. 



In recent decades, society has witnessed trends towards increasing polarization, segregation and inequality. These trends can be observed in local neighborhoods (e.g. Dutch school segregation), nationally (e.g. fragmentation of the Dutch House of Representatives), and globally (e.g. income inequality). Despite enormous efforts to understand these phenomena and their contribution to social unrest and political extremism, the interdependencies between them have rarely been considered. Exploring these connections is a pressing scientific problem that can lead to breakthroughs in our understanding of society as a complex system.

Accurately modeling society in order to predict its dynamic evolution appears to be an insurmountable task, the complexity and implications of which can currently only be portrayed in science fiction, such as the “Foundation” series of books by Isaac Asimov.  These difficulties are rooted in the interconnectedness of different emergent social phenomena at different temporal and spatial scales, leading to intergenerational legal and political challenges. However, progress can be made by focusing on specific aspects of society for which the temporal and spatial scales can be widely separated. This is the case for the phenomena of polarization, segregation and inequality and their interdependencies. For example, explanations of school segregation (e.g. in the Netherlands) are rooted in an underlying inequality in educational attainment, which ultimately leads to polarized behavior, increased segregation and the promotion of further inequalities.

Tackling this challenging but feasible problem requires integrating knowledge from different disciplines into a single conceptual framework, strategically combining both academic-driven and societal (non-academic)-driven research. This is precisely the strategy of this RPA. Through interdisciplinary collaboration, RPA PSI innovatively links several strong lines of research at the UvA aimed at understanding PSI, which have so far worked in isolation, and connects to Dutch society by closely collaborating with Statistics Netherlands (CBS) and using datasets from the Municipality of Amsterdam and other sources. This directly interweaves foundational PSI methodologies including (FNWI) socio-econophysics and agent-based modelling; (FMG) formalisation of psychological theories and contextual/historical analyses; (FEB) behavioral economics and data science; (FdR) legal dogmatic/theoretical analyses and critical approaches to law; and (CBS) constraining complex models with observational data.
Our approach will be to gather this broad expertise and a team of postdoctoral fellows and a tenure tracker to develop a framework grounded in complexity systems theory for building models of simplified artificial societies exhibiting PSI. With this framework in hand, our goal is to address several open questions:

What are the necessary ingredients that a model must include to exhibit the emergent phenomena of polarization, segregation and inequality?
Can we use such models to develop measures/indices of societal trust? 
Are there critical levels for such indices, below which society is highly likely to suffer major societal disintegration? 
What interventions, whether political, legal or social, can regulate these emergent phenomena?

To answer these questions, we will build a computational and mathematical model of an artificial society with polarization, segregation and inequality, and constrain it using data, mostly available from CBS, with a focus both locally (Amsterdam) and nationally (Netherlands). In order to lay the foundations of the model, we need to take into account the results of contextual, historical and legal analyses. For example, current models of opinion polarization do not take into account the correlation or feedback mechanism between inequality and opinion. Projects 1, 2 and 3 therefore take societal cases that are highly relevant to the Netherlands and Amsterdam to study the mechanisms that underlie (the relationships between) polarization, segregation and inequality (see Figure 2). Parallel to this, project 4, which will run continuously over the 5-year period, uses the insights from the foundational projects to generate a computational model of PSI constrained by data from Dutch society. Specifically, these projects aim to:

(1) Uncover the reciprocal causal links between segregation and inequality . 

(2) Understand the feedback loops between inequality and polarisation

(3) Understand the causal links between polarisation and segregation

(4) Integrate (1), (2) and (3) into a single model and constrain it using available data.

You can visit our
Project Hub for potential ideas for research projects within the first 3 categories above.

The main outcome of RPA PSI will be not only a fundamental understanding of these three emergent phenomena and their interrelationships but also a toolbox that can potentially be applied to understand other social phenomena (e.g. the emergence of criminal networks, the spread of misinformation in social networks, and threats to urban mental health) and societal transitions (e.g. from polarized to unpolarized societies). In addition the models can be used to study the effects of interventions, such as how urban (re)developments or reforms of housing laws can affect residential segregation in order to contribute to a more equal and fair society for future generations.


The RPA PSI has several open calls. Besides the open call for a Tenure Track position (which has now been filled), there is an open call for three 3-year postdoc positions and for short term (3 months to 1 year) RPA PSI fellowships (see below).


Tommaso Giommoni | tenure tracker
Tommaso Giommoni has been hired within this RPA PSI as a new tenure tracker based at the Faculty of Economics and Business and is starting in September 2024. His main research interests include Public Economics, Political Economy and Public Finance, with particular focus on issues related to taxation, fiscal federalism and public corruption. Tommaso will take the lead on understanding big data sets and extracting relevant information on polarisation, segregation and inequality in Dutch society.
Petter Tornberg | PSI fellow
Petter Tornberg is the first RPA PSI fellow who is developing a project on simulating social media using large language models to evaluate alternative news feed algorithms with collaborators Justus Uitermark, Diliara Valeeva and Christopher Bail. Petter's research is on how digital technology is reshaping our politics, media and cities. I use computational methods and digital data to examine the consequences of datafication, platformization, and AI, from a critical  perspective.
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The RPA PSI gathers researchers from different faculties, institutes and initiatives including DIEP@UvA, FAEME, Amsterdam Institute for Social Science Research, COMPASS, NETWORKS, the Center for Nonlinear Dynamics and Finance and the Amsterdam Centre for Transformative Private Law. RPA PSI is coordinated by J. Armas and C. Mulatier. 
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Statistical physics, game theory | IoP


Complex systems |IoP & IvI 

Jan de Boer

Statistical physics, information theory | IoP


Agent-based modelling | IvI


Stochastic systems, networks | KdVI

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Psychology | FMG


Social science | FMG


Economics, dynamical systems | FEB


Experimental economics | FEB


Private law | FdR


Mathematics and data science | KdVI and CBS

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