1. Ethnic diversity, density and their consequences on political participation: An agent-based simulation Laurence Lessard-Phillips, Institute for Social Change, University of Manchester Nick Crossley, Department of Sociology, University of Manchester Bruce Edmonds, Centre for Policy Modelling, Manchester Metropolitan University Ed Fieldhouse, Institute for Social Change, University of Manchester Yaojun Li, Institute for Social Change, University of Manchester Ruth Meyer, Centre for Policy Modelling, Manchester Metropolitan University Nick Shryane, Institute for Social Change, University of Manchester

2. Background Ethnic minorities are (slowly) becoming a bigger part of the UK’s national population ~5.6% (1991) – ~7.9% (2001) – ~ 14-18% (2051) Engagement of ethnic minorities in ‘conventional politics’, and its main determinants, is an interesting topic of enquiry – Ethnic minorities becoming increasingly important segment of the electorate Especially given their location, density and diversity in the UK – Link to socio-political integration/incorporation and other related issues (representation, etc.) – UK case peculiar given voting right of Commonwealth citizens 2

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4. Theorising the role of ethnic diversity and density on turnout Ethnic diversity (based on Fieldhouse and Cutts, 2008) – Group conflict theory: diversity leading to higher levels of conflict and hence mobilisation of the population, leading to higher levels of turnout Can also have depressing effect on turnout – Economic resources theory: highly diverse communities have weaker mobilising effects and higher barriers to participation due to lack of resources – Racial diversity thesis: high levels of diversity display more inequalities and hence lower participation – Social capital theory (?): link between diversity and levels of interpersonal/generalised trust 4

5. Theorising the role of ethnic diversity and density on turnout Ethnic density (based on Fieldhouse and Cutts, 2008) – Social capital theory: group concentration leading to higher levels of bonding capital, connectedness and networks, which generate higher levels of political mobilisation and hence turnout – Ethnic community model: higher levels of group consciousness/awareness leading to higher levels of turnout May also cause alienation – Relative deprivation theory: higher levels of deprivation may lead to increased levels of alienation and, in turn, to decreased turnout 5

6. Political participation of ethnic minorities in the UK: Existing evidence Research-based evidence has found divergence in the turnout rates of various ethnic minority groups, with (some) stabilisation of turnout rates over time – Asian turnout > than turnout for non-Asians Differentiation within Asian groups – Black Caribbean and African groups: lower levels amongst ethnic minority groups – Yet more recent evidence seems to contradict these claims Somehow difficult to disentangle ethnic group effects from other effects such as age, socio-economic status, etc. No clear agreement as to the impact of density on ethnic minority turnout – Data/methods issues 6

7. But… We are still a long way from understanding this issue without integrating the varied accounts that exist into a unified model that captures the complexity of processes that might be at play – Linking the micro to the macro One way in which you can try to do this is via agent-based simulation – Underutilised method informed by data/evidence/theory in the social sciences that can link multiple and multi-faceted influential processes 7

8. Agent-based simulation What is it? Computational description of a given process – Not usually analytically tractable More context-dependent… – … but assumptions are much less drastic Detail of unfolding processes accessible – more criticisable (including by non-experts) Used to explore inherent possibilities Validatable by data, opinion, narrative... – Often very complex What happens? Entities in simulation are decided up Behavioural rules for each agent specified – e.g. sets of rules like: if this has happened then do this Repeatedly evaluated in parallel to see what happens Outcomes are inspected, graphed, pictured, measured and interpreted in different ways 8

9. Dilemmas using this approach KISS (Keep it Simple, Stupid) Models should be simple enough to understand and check (rigour) May omit critical aspects of the system of interest (lack of relevance) Strong inferences possible about within-model processes Weak mapping to the thing being modelled KIDS (Keep it Descriptive, Stupid) Models should capture the critical aspects of social interaction (relevance) They may be too complex to understand and thoroughly check (lack of rigour) Weak inferences about within-model processes Clear mapping to the thing being modelled 9

10. Agent-based simulation model of voting behaviour: ‘the’ model Input Individual characteristics Demographic, psychological Individual behaviours Memory of events External shocks Model layers Generic population dynamics Birth, death, movement Social networks Households, spatial, political discussion networks, etc. Influence Vertical and horizontal socialisation and mobilisation Voting decision Intention vs. action Output Characteristics of system Aggregate outcomes (fed back to model layers) 10

11. Encapsulating narrative stories of voting in the simulation Based on collected evidence, we set out stories according to which our agents act – E.g. I voted for party X because it will put limits on immigration. I voted for minor party Y because I wanted to send a message to those lying, cheating, fiddlers in Westminster. I always vote – it’s part of who I am. I didn’t vote – what’s the point? Was there an election on? These narratives also take into account the characteristics of the agents, their dynamics, and other influences 11

12. Using the Simulation: the context Run simulations that correspond to different settings or behavioural hypotheses See how it affects outcomes, e.g.: – Ethnic minority turnout – Ethnic majority turnout Results do not predict, but reveal possible emergent outcomes More importantly – Raises new questions and gaps in knowledge – An “in vitro” exploration of some of the complex relationships between factors that can occur – Suggests new hypotheses (or refinements on old hypotheses) in an explicit and demonstrated form 12

13. RESULTS FROM PRELIMINARY “PROOF OF CONCEPT” VERSION 13

14. Early, “Proof of Concept” Version of the Model Simulation model still being developed Validation stage yet to begin in earnest Demonstrated with 4 different scenarios Only difference in minorities are (a) those inherent in the data we used to initialise the model and (b) the homophily effect of agents tending to make social links with similar age/ethnicity/politics Model was run 25 times Average turnout in minority and majority is then measured 14 Low immigration, High majority population High immigration, High majority population Low immigration, Low majority population High immigration, Low majority population

15. Turnout by majority, minority (1%IR)

16. Turnout by majority, minority (5%IR)

17. Conclusion ABS links micro- and macro-level processes in an explicit manner, enabling the exploration of the effects of how individuals behave and relate to each other at the aggregate level Still in the process of developing the model – Gathering evidence – Making linkages – Updating narratives Special focus on extensive exploration of dynamic social networks (e.g., household-level influences) Future development of narrative  model “translations” 17

18. THANK YOU! http://www.scid-project.org 18

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