Post on 14-Apr-2017
Closing the Qualitative/Quantitative
Divide: Computer Simulationand Sociology
Edmund ChattoeDepartment of Sociology
University of Oxfordedmund.chattoe@sociology.ox.ac.uk
http://www.sociology.ox.ac.uk/chattoe.html
Plan of the Talk
• The “Research Triangle”: Unity in Social Science?
• The “agent based” perspective• Computer simulation and some “traditional
misunderstandings”• Illustrating the simulation approach:
published results and work in progress
THEORY
DATA
METHODS
Functionalism, RCTLabelling, SC, Marxism
Families, Factories,Churches, Schools
Surveys, Interviews,Documents, Experiments
The Unity of Social Science?• Data as a sustainable difference• But interest in data rather mysterious
(Dickinson’s Law?)• Methods and Theory no longer “free” once
data is chosen• Tendency to conflation (GLR, SC as “non
cognitive”, processes as variables)• “Meta” questions like “Where to start?”
The “Agent Based” Approach IAGENT 1
c1=a1y1
AGENT 2c2=a2y2
CSOC, Y
ECONOMISTC=aY
The “Agent Based” Approach IIAGENT 1MODEL
AGENT 2MODEL
INSTITUTIONRULES
“SOCIAL”SCIENTIST
REGULARITY
Models and Processes• Cognitivism is not psychologism*• The extent of deliberation, social
comparison, routine and type of mental representation is an empirical question*
• We have good “social” processual reasons to assume regularity in models*
• But, if we are wrong, we must all pack up or become novelists
Computer Simulation• Computational, rather than verbal or “statistical” (GLR?), representation of a social process
• Descriptive rather than instrumental use• Not “tied” to a particular view of models*• An “explicit” representation*• Fundamental problem is not programming
but proper data*
Example: A “Social” Market• Economics aggregates to get D, S curves and
then solves for market clearing• S and D curves don’t exist in the minds of
buyers or (probably) sellers• What exists are inventories, shopping trips,
haggling, gossip, strikes …• S and D curves can be “produced” from a
simulated market but so can networks, narratives and so on: falsification?
Example I: Lifestyle Emergence• Based on qualitative data about money
management among pensioners• Importance of “practices” and “lifestyles”• Almost no explicit calculation: an
excellent corrective to economics• Abstraction but inductive abstraction• Linking sequence/narrative data to
individual choice
Lifestyle Emergence Simulation• Activity plans (444411122111) and budget
plans (1111000110111)• Distinguish plan and realisation• Adaptive rule for individual comparison of
(largely unobservable) budget plans• Adaptive rule for social comparison of
observable (communicated) activity plans• Improved wellbeing and emergent lifestyles
Example II: Social Mobility• Paradigmatic statistical (GLR) sociology
linking highly theorised concepts• Dilemma with micro/macro link
– micro theory must be “anti social” (RCT) to guarantee transparent aggregation
– Plausible micro theories have uncertain macro consequences (Schelling example)
• Simulation as a tool for integration
MOBSIM: Work in Progress• Microsimulation: agents, attributes and
updating processes (environment)• Families, schools and jobs/classes• Families: demographics and social
practices• Schools: “epoints”• Jobs: Hiring by epoints, random firing• No social networks or “economics” yet
The Scope of Models
Labour Markets
Demography
Education
??
Implications of MOBSIM• Thought provoking surprises: identification
of lacunae• Integration of diverse research• Potential falsification using within
generation (labour market surveys), qualitative biographical and sequence data
• Exploring micro/macro relations: another possible mode of falsification
The Future?• Methods: Adapting methods to simulation
– Dynamic process data– Ethnographic decision elicitation– A sociological protocol for “experimentation”
• Data: Neglected approaches to sociality– Adaptive models: innovation diffusion (drugs)– Dynamic social networks and endogeneity– Time planning and lifestyles as sequences– Selectionism: Evolving social practices
Conclusions• A genuinely novel method of representing
social processes• Inspires new developments in methodology
(the agent based approach) and the possible return of falsifiability
• Suggests new kinds of theories and represents existing debates (micro/macro)
• Uses and generates data in novel ways: synthetic