Planning Social Mix – A Critical Review of Programs

1. Planning Social Mix – A Critical Review of Programs ENHR-Conference Toulouse, July 5-8, 2011 Jürgen Friedrichs University of Cologne, Germany Folie: 1

2. Contents 1. Relevance of the Concept 2. Programs 3. Problems of Social Mix 4. Logic of Planning Social Mix 5. Empirical Evidence 6. Why Results Differ – An Explanation 7. Conclusions

3. 1. Relevance: Theories Intersection of planning and social science theories:  context effects (Dietz 2003, Galster 2009, Sampson, Morenoff and Gannon-Rowley 2002)  tipping points (Schelling 1971)  contact and prejudice (Pettigrew and Tropp 2006)  competition and threat (Blalock 1967)  social capital (Putnam 2000)  cohesion and social control (Sampson et al. 2002)  social learning (Bandura und Walters 1963)

4. 1. Relevance: Planning Promises (1) Social mix accomplishes to • rise the standards of lower classes, • support job search, and transition from social assistance or unemployment to employment, • increase the quality of facilities, schools in particular, by the demand of the better-off, with benefits for the disadvantaged,

5. 1. Relevance: Planning Promises (2) • increase social stability by less in- and out-moves, • increase social capital and social cohesion, • decrease the stigmatization of the area, • decrease rates of deviant behavior.

6. 2. Programs (1) “Social mix is at the core of urban planning” (Kleinhans 2004: 367)

7. 2. Programs (2) Examples: • Australia (Adelaide City Council 2002, Arthurson and Anaf 2006, Word 2003)  Great Britain (Manzi and Bowers 2003, ODPM 2005, Page 2000, SEU 2000, Tunstall 2003)  Ireland (Norris 2005)  Netherlands (Ostendorf, Musterd and de Vos 2001, Priemus 1998, VROM 2011)  Scotland (Scottish Executive 2006, Scottish Homes 2001, 2006)  USA (Brophy and Smith 1997, Schwartz and Tajbahsh 1997)

8. 2. Programs (3) Target areas: deprived high share low income high share social renter What about social mix in middle class areas? What about more middle class in upper class areas?

11. 3. Problems (1) A. Mix: 1. Which dimensions, e.g., housing status, income, ethnicity? 2. Which shares in a given diemnsion, e.g., 30 % homeowner? 3. Which spatial unit, e.g., estate, street, block? 4. Which indices of social mix, e.g., Heterogeneity (Agresti and Agresti 1977), Diversity (Simpson 1949)?

12. 3. Problems (2) B. Planning: 5. Which measures are available for planning social mix? 6. Which measures will yield which desired outcomes? 7. Which outcomes can be expected for which social group? 8. Planning for a new estate or diversifying an existing neighborhood?

13. 3. Problems (3) C. Outcomes 9. Which outcomes does increased mix have? 10. Evidence of unanticipated consequences of measures and social mix?

14. O3 Zi M1 O1 O2 M2 G1 Social Mix M3 4. Logic of Planning (1) ___ desired outcomes ------ not desired / unanticipated outcomes

15. 4. Logic of Planning (2) M = Measures:  ownership (= dominant measure) better schools green spaces z = not desired outcomes of measures: e.g. Rotterdam: in-moves restricted to employment may discriminate migrants O3 = not desired outcomes of increased social mix: rising rents and prices for homes

16. 4. Logic of Planning (3) Tenure mix is the major strategy ► physical measures are implemented to achieve social mix ► this requires bridging assumptions physical measure → social group

17. 5. Empirical Evidence (1)  Optimal mix level: street or block (Jupp 1999)  Owner and social renter mix over the entire area (“pepperpotting”) (Bailey et al. 2006) Buildings of owners and social renters should have little observable differences, “tenure blindness”(Rowland et al. 2006) Threshold: 30 % social renter (Graham et al. 2009) Residents do not perceive social mix (Allen et al. 2005, Holmes 2006, Jupp 1999)

18. 5. Empirical Evidence (2) Most important finding: Inconsistent and ambiguous results (Atkinson 2005, Atkinson and Kintrea 2001, Bailey et al. 2006, Galster 2007, Graham et al. 2009, Joseph 2008, Meen et al. 2005, Musterd 2008, Tunstall 2001;2010)

19. 6. Why Results Differ: Explanation (1) Macro-micro model of social mix URBAN AREA Social Mix Outcomes (e.g., social cohesion, unemployment quota) INDIVIDUAL Probability of contact Contact, Social learning

20. 6. Why results Differ: Explanation (2) Specification by a macro-micro model exhibits: social mix planning rests on several not tested contextual and individual behavioral assumptions. (Although we have relevant theories.) Thus, similar planning measures will have very different outcomes.

21. 6. Why Results Differ: Explanation (3) Example: Ethnic Diversity  Diversity → (+) Stability (McCulloch 2003) Diversity → (+) Fear of crime (Kennedy and Silverman 1985) Diversity → (+) Deviant behavior (Sampson and Groves 1989) Diversity → (-) Social networks (Blokland and van Eijk 2010) Diversity → (?) Trust (Verwoort, Flap and Dagevos 2010)

22. 6. Why Results Differ: Explanation (4) If 8 % migrants in a neighborhood, only 58 % Germans would move in, if 33 % migrants, only 39 % (Friedrichs 2008) Threshold values and growing sanction potential of dominant group (Galster 2007: 26)

23. 7. Conclusions (1) Social mix is benevolent concept of socio-spatial equity in deprived neighborhoods Planning measures imply several assumptions lacking empirical evidence The relation between macro and micro level mechanisms has still to be specified Unintended outcomes are to examined

24. 7. Conclusions (2) No answer beyond Herbert Gans (1961): “moderate heterogeneity” Too few longitudinal studies (but e.g.: Musterd and Andersson 2005) Case studies lack methodological rigor Microsociological foundation of social mix is lacking (but Galster 2007)

25. 7. Conclusions (3) Additional paradigm: Where do residents experience social mix? → to study “exposure situations” = frames and behavior

26. To Take Home: Suppose, these are the social mix dimensions and their shares ...

27. … and this is what you get at best: (Wehrli / Keith Haring)