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Confessions of a social scientist

Confessions of a social scientist. My meanderings in the world of ABM. About me. (Quantitative) Sociologist Some experience with programming Main research interests: Immigrant adaptation in a comparative perspective Ethnic inequalities in education and the labour market

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Confessions of a social scientist

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  1. Confessions of a social scientist My meanderings in the world of ABM

  2. About me • (Quantitative) Sociologist • Some experience with programming • Main research interests: • Immigrant adaptation in a comparative perspective • Ethnic inequalities in education and the labour market • Social stratification and mobility

  3. My relationship with ABM • Prior relationship with ABM? • Very brief • Currently a research associate on the ‘Social Complexity of Immigration and Diversity’ (SCID) project at the Institute for Social Change • One of (many) roles in the project: • Help build rules of behaviour (agents, households, etc.) for a complex agent-based model of voting behaviour • Embedded in existing literature and data

  4. Demographic characteristics Ethnicity, Age, Immigration status, Class Meso-level: Networks and overlapping groups Exogenous factors Activity Micro-level: the individual Voting Intention to vote Habit Social Population dynamics Learning Civic duty ‘Rational choice’ Interest & knowledge Household Micro-level: relational processes Socialisation Discussion Mobilisation

  5. Lessons learned (I) • It is hard to wrap your head around the ABM way of thinking • Process of coding/labelling • Can be strenuous (it’s hard for everyone!) • How to set out rules of behaviour • There is a lot out there to make sense of! • How to approach an ABM problem • Global idea of what want to achieve (but might not be able to!) • What can be achieved with ABM • And what cannot (prediction is hard!) • Speaking the same language as the programmers • Not always a smooth process (but very helpful) • The sheer length of the process! • Especially when it comes to debugging/validating (and arguing)!

  6. Lessons learned (II) • It is even harder to wrap other people’s heads around ABM • Focus away from traditional views (from quant side) • Coefficients and prediction • Perception that you are claiming that you can explain everything • Someone will always have some element to add to your model! • It has shifted the way in which I perceive social science • (Lack of) focus on mechanisms • More focus on the sheer complexity of human behaviour and phenomena • And how little we know about it! • Critical overview of existing theory and data sources • But all in all it is a pretty useful tool of social enquiry

  7. Impact on my own research • Having a go at my own ‘simple’ model • Test ideas present within the immigration literature, mainly: • Dynamics process of migration (including feedback mechanisms, network and herd effects) • Massey, Rogers, de Haas, Epstein • Impact of selectivity at sending and receiving country level • Lee, Borjas, Feliciano • Role of policy regimes • Castles and Miller, Koopmans

  8. The model A Low skilled High skilled No selection B E C General Family #% #% #% D

  9. Questions? Comments?

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