- Epicentres of human creativity
- Economic growth
- Industry
- Innovations
Time | Space | Beyond
Outline
Cities
Bias | Confounding | Counterfactuals
Time
Space
Beyond: social networks
Cases in SES research
Cities
- Epicentres of pollution
- Resource use and waste
- Energy, water, food
- Hotspots of disease, crime
Cities are both the problem and solution of many sustainability challenges
Cities
Complex adaptive systems
- Non-linear dynamics
- Feedbacks
- Delays
- Heterogeneity
- Resilience
The good and the bad scales up 
Bettencourt L, Lobo J, Strumsky D.Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities. PLoS ONE. 2010.
Bias | Confounding | Counterfactuals
Bias
Bias
Discuss in groups (5min)
- What is bias?
- How can bias arise in qualitative studies?
- How can bias arise in quantitative studies?
- An example (made up or from your readings)
Confounding
Confounding
“…a variable that influences both the dependent variable and independent variable, causing a spurious association.”
Confounding
Discuss in groups (5min)
- Why is confounding relevant?
- What could be a good example of confounding factors in your qualitative studies?
- What could be a good example of confounding factors in your quantitative studies?
- How does one lead with confounding factors?
Counterfactual
“… we may define a cause to be an object, followed by another, and where all objects, similar to the first, are followed by objects similar to the second. Or in other words, where, if the first object had not been, the second never had existed …” — David Hume
Discuss in groups (5min)
- Examples of counterfactuals on your qualitative readings?
- Examples of counterfactuals on your quantitative readings?
- Why would you worry about them? Under which conditions?
Back to cities
Time 1D
- Memory decays with time
- % of your memories are made up
- Seasonality
- Non-stationary (trend)
- Burstiness
- Coarse graining (missing the signal?)
- Effects change over time
Salvador Dalí, The persistence of memory (1931)
Space 2-3D
- Perceptions in space
- Autocorrelation
- Heterogeneity
- Difussion
- Coarse graining (missing the signal?)
- Effects change over space
Maurits Escher, Relativity (1953)
Beyond N-D
The world wide web 
Break (15min)
Re-cap
Cities
Bias | Counfunding | Counterfactuals
Time
Space
Beyond: social networks
Cases in SES research
Tack | Gracias
Questions?
email: juan.rocha@su.se
twitter: @juanrocha
slides: juanrocha.se/presentations/USES_qualitative_methods
Stockholm Resilience Centre
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Time | Space | Beyond
Juan C. Rocha
Social networks
“birds of a feather flock together”