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