Using a Data-Integration Model to Stage Abstraction in Voter Turnout<br />Bruce Edmonds, et. alCentre for Policy Modelling...
Social Complexity of Immigration and Diversity<br />A 5 year EPSRC-funded project between:<br />University of Manchester<b...
The Underlying Problem<br />The Anti-Anthropocentric Principle: the world we study is not arranged for our convenience (as...
The Resulting Dilemma<br />KISS: Models that are simple enough to understand and check (rigour) are difficult to directly ...
the Modelling Approach<br />SNA Model<br />Analytic Model<br />Abstract Simulation Model 1<br />Abstract Simulation Model ...
Data-Integration Models<br />To develop a simulation that integrates as much of the relevant available evidence as possibl...
DIM Development Method<br />A relatively tight interactive “loop” between the social scientists who are experts in the sub...
Some examples of Causal Stories<br />Someone may vote or abstain because....<br />of habit – they are used to doing so and...
Model Overview<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, Sep...
Agent Characteristics<br />Age, Ethnicity, location, children, parent, partner, political leaning, date last moved, etc.<b...
Population Model I<br />Agents are in households: parents, children etc. of different ages in one location<br />Initialise...
Population Model II<br />As well as households there are activities: schools, places of work, and (currently 2) kinds of a...
Social Network<br />A “connection” is a relationship where a conversation about politics might occur (but only if the part...
Influence<br />Social norms transmitted in household (if not contradictory)<br />Interest in politics transmitted via cont...
Voting Decision<br />4 stage model of whether to vote:<br />Habit – when an agent has voted in 3 out of 4 of the last elec...
Example Output<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, Sep...
Early, “Proof of Concept” Version of the Model<br />“Rural”Case<br />Simulation model still being developed, validation st...
Turnout − “Urban” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vie...
Underlying Factors − “Urban” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds...
Log − “Urban” Case<br />1945: (person 712) did not vote<br />1946: (person 712) started at (workplace 31)<br />1947: (pers...
Turnout − “Rural” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vie...
Underlying − “Rural” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, ...
Log − “Rural” Case<br />1949: (person 561) partners with (person 413) at (patch 11 16)<br />1950: (person 561) stops going...
But why not just jump straight to simple models?<br />There are many possible models and you don’t know whyto choose one r...
Further Work/Unresolved Issues<br />Development of qualagent rule process needs more research so it is more systematic, r...
The End  <br />The SCID Project<br />http://scid-project.org<br />Bruce Edmonds<br />http://bruce.edmonds.name<br />Centre...
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Using a Data-Integration Model to Stage Abstraction in Voter Turnout

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Using a Data-Integration Model to Stage Abstraction in Voter Turnout

  1. 1. Using a Data-Integration Model to Stage Abstraction in Voter Turnout<br />Bruce Edmonds, et. alCentre for Policy ModellingManchester Metropolitan University<br />
  2. 2. Social Complexity of Immigration and Diversity<br />A 5 year EPSRC-funded project between:<br />University of Manchester<br />Institute for Social Change<br />Ed Fieldhouse, Nick Shryane, Nick Crossely, Yaojun Li, Laurence Lessard-Phillips, HuwVasey<br />Theoretical Physics Group<br />Alan McKane, Tim Rogers<br />Manchester Metropolitan University<br />Centre for Policy Modelling<br />Bruce Edmonds, Ruth Meyer, Stefano Picassa<br />Aim is to apply complexity methods to social issues with policy relevance<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 2<br />
  3. 3. The Underlying Problem<br />The Anti-Anthropocentric Principle: the world we study is not arranged for our convenience (as academics)<br />Corollary: there is no reason to suppose that the social world is such that a model adequate to its representation will be simple enough for us to understand<br />There are reasons to suppose that it is not (social embeddedness, SIH, Machiavellian Intelligence, cognitive competition etc.)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 3<br />
  4. 4. The Resulting Dilemma<br />KISS: Models that are simple enough to understand and check (rigour) are difficult to directly relate to both macro data and micro evidence (lack of relevance)<br />KIDS: Models that capture the critical aspects of social interaction (relevance) will be too complex and slow to understand and thoroughly check (lack of rigour)<br />Butwe need bothrigour and relevance<br />Mature science connects empirical fit and explanation from micro-level (explanatory and phenomenological models)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 4<br />
  5. 5. the Modelling Approach<br />SNA Model<br />Analytic Model<br />Abstract Simulation Model 1<br />Abstract Simulation Model 2<br />Data-Integration Simulation Model<br />Micro-Evidence<br />Macro-Data<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 5<br />
  6. 6. Data-Integration Models<br />To develop a simulation that integrates as much of the relevant available evidence as possible, both qualitative and statistical Regardless of how complex this makes it<br />A description of a specified kind of situation (not a general theory) that represents the evidence in a single, consistent and dynamicsimulation<br />This simulation is then a fixed and formal target for later analysis and abstraction<br />Central idea is to stage abstraction and provide a fixed target for more rigorous models<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 6<br />
  7. 7. DIM Development Method<br />A relatively tight interactive “loop” between the social scientists who are experts in the subject matter and data and the simulation developers...<br />...trying to give as much ownership and control to social scientists as possible.<br />First target: What makes people vote within a diverse community?<br />Started with developing a fairly complete list of “causal stories” concerning the various processes that might contribute from <br />Then initial model iteratively developed in NetLogo to enable maximum responsiveness and transparency<br />To be reimplemented in Java/Repast when the target becomes more “settled” for more extensive simulation exploration and analysis<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 7<br />
  8. 8. Some examples of Causal Stories<br />Someone may vote or abstain because....<br />of habit – they are used to doing so and don’t really consider alternatives<br />of self/group interest – they calculate that it is in their own benefit to do so<br />of social norms – they have internalised a form of “civic duty” which obligates them<br />of mobilisation – because somebody (perhaps from a party) asked them to vote <br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 8<br />
  9. 9. Model Overview<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 9<br />
  10. 10. Agent Characteristics<br />Age, Ethnicity, location, children, parent, partner, political leaning, date last moved, etc.<br />The activities it participates in<br />Its social connections<br />Plus a memory of facts, e.g.:<br />“talked about politics with” agent324 blue 1993<br />“got desired result from voting” red 1997<br />“I am a voter” 2003<br />“pissed off with my own party” 2004<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 10<br />
  11. 11. Population Model I<br />Agents are in households: parents, children etc. of different ages in one location<br />Initialised from a sample of 1992 BHPS<br />Agents are born, age, make partnerships have children, move house, separate, die<br />UK-based moving in/out of region, as well as international immigration/emigration<br />Rates of all the above estimated from available statistics<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 11<br />
  12. 12. Population Model II<br />As well as households there are activities: schools, places of work, and (currently 2) kinds of activity (e.g. church, sports clubs)<br />Kids (4-18) attend one of 2 local schools<br />Those employed (from 16-65) attend a place of work randomly<br />Activities are joined probabilistically, with choice related to homophily (similarity to existing members)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 12<br />
  13. 13. Social Network<br />A “connection” is a relationship where a conversation about politics might occur (but only if the participants are inclined/receptive)<br />All members of a household are connected; when someone moves out there is a chance of these being dropped as connections<br />There is a probability of people attending the same activity to be connected (chance varying according to similarity)<br />There is a chance of spatial neighbours who are most similar being connected<br />There is a chance of a “Friend of a Friend” becoming a connection<br />Connections can be dropped<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 13<br />
  14. 14. Influence<br />Social norms transmitted in household (if not contradictory)<br />Interest in politics transmitted via contact network by interested/involved agents with those who are receptive<br />Some discussants may be more influential than others<br />Bias in terms of who to vote for may evolve due to coherence / incoherence in the messages about politics<br />Interest & bias in politics may convert to voting probabilistically <br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 14<br />
  15. 15. Voting Decision<br />4 stage model of whether to vote:<br />Habit – when an agent has voted in 3 out of 4 of the last elections they tend to continue to do so<br />Factors – politically involvement, civic duty norms, habit, friends’ conversations, education, level of interest, past “success” at voting/abstaining etc.<br />Intention – above come together to an intention to vote (or otherwise)<br />Modifying factors – recent young child, recent move, householder going to vote, canvassed by party etc. then may alter this intention<br />Then compared with historical result of election which affects the satisfaction of the individual with the result (election results are exogenous)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 15<br />
  16. 16. Example Output<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 16<br />
  17. 17. Early, “Proof of Concept” Version of the Model<br />“Rural”Case<br />Simulation model still being developed, validation stage yet to begin in earnest<br />Demonstrated here with 2 different scenarios:<br />“Rural”: 85% density, 95% maj., 1% Immigration rate<br />“Urban”: 30% denisity, 65% maj., 5 % Immigration rate<br />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<br />Model was run 25 times<br />“Urban”Case<br />17<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 17<br />
  18. 18. Turnout − “Urban” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 18<br />
  19. 19. Underlying Factors − “Urban” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 19<br />Interest in Politics<br />Index<br />Political Involvement<br />Habit Voting<br />Civic Duty Norm<br />Time<br />
  20. 20. Log − “Urban” Case<br />1945: (person 712) did not vote<br />1946: (person 712) started at (workplace 31)<br />1947: (person 712)(aged 29) moved from (patch 4 2) to (patch 5 3) due to moving to an empty home<br />1947: (person 712) partners with (person 698) at (patch 5 3)<br />1950: (person 712) did not vote<br />1951: (person 712) seperates from (person 698) at (patch 5 3)<br />1951: (person 712)(aged 33) moved from (patch 5 3) to (patch 4 2) due to moving back to last household after separation<br />1951: (person 712) did not vote<br />1952: (person 712) partners with (person 189) at (patch 4 2)<br />1954: (person 712)(aged 36) moved from (patch 4 2) to (patch 23 15) due to moving to an empty home<br />1955: (person 712) did not vote<br />1964: (person 712) started at (activity2-place 71)<br />1964: (person 712) voted for the red party<br />1966: (person 712) voted for the red party<br />1970: (person 712) voted for the red party<br />1971: (person 712) started at (workplace 9)<br />1974: (person 712) voted for the red party<br />1979: (person 712) voted for the red party<br />1983: (person 712) died at (patch 23 15)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 20<br />
  21. 21. Turnout − “Rural” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 21<br />
  22. 22. Underlying − “Rural” Case<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 22<br />Interest in Politics<br />Index<br />Political Involvement<br />Habit Voting<br />Civic Duty Norm<br />Time<br />
  23. 23. Log − “Rural” Case<br />1949: (person 561) partners with (person 413) at (patch 11 16)<br />1950: (person 561) stops going to (school 2)<br />1950: (person 561) did not vote<br />1951: (person 561) started at (activity2-place 23)<br />1951: (person 561) did not vote<br />1955: (person 561) did not vote<br />1956: (person 561) started at (workplace 9)<br />1964: (person 561) voted for the red party<br />1965: (person 561) started at (activity2-place 25)<br />1966: (person 561) voted for the red party<br />1970: (person 561) voted for the red party<br />1974: (person 561) voted for the red party<br />1979: (person 561) voted for the red party<br />1981: (person 561) started at (workplace 15)<br />1983: (person 561) voted for the red party<br />1987: (person 561) voted for the red party<br />1992: (person 561) voted for the red party<br />1995: (person 561) started at (workplace 11)<br />1997: (person 561) started at (activity1-place 18)<br />1997: (person 561) voted for the red party<br />2000: (person 561) started at (workplace 13)<br />2001: (person 561) voted for the red party<br />2005: (person 561) voted for the red party<br />2009: (person 561) died at (patch 11 16)<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 23<br />
  24. 24. But why not just jump straight to simple models?<br />There are many possible models and you don’t know whyto choose one rather than another, this method provides the underlying reasons<br />Much social behaviour is context-specific, and this approach allows one to check whether a particular simple model holds when background features/assumptions change<br />The chain of reference to the evidence is explicit, allowing one to trace their effect and possibly better criticise/improve the model<br />This approach facilitates the mapping onto qualitative stories/evidence<br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 24<br />
  25. 25. Further Work/Unresolved Issues<br />Development of qualagent rule process needs more research so it is more systematic, replicable and transparent<br />Shows need for a library of ‘mundane’, underlying agent-based models of, say, population, household structure change<br />Descriptive/diagramming techniques to make simulation design more accessible <br />Using a Data-Integration Model to Stage Abstraction in Voter Turnout, Bruce Edmonds, ECCS, Vienna, September 2011, slide 25<br />
  26. 26. The End <br />The SCID Project<br />http://scid-project.org<br />Bruce Edmonds<br />http://bruce.edmonds.name<br />Centre for Policy Modelling<br />http://cfpm.org<br />

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