1. 27/03/2012 University of Oxford Seminar, University of Helsinki, Finland, May 11, 2012

2. 2 Outline 2 Impact of diversity: Putnam’s pessimistic prognoses Types of intergroup contact: Whether and how they work  Direct and extended forms of contact Impact of contact  Focus: generalized/’secondary transfer’ effects Archival re-analysis of contact effects in extreme conditions  Rescuers of Jews from Nazi Europe Observational research on intergroup contact Conclusions

3. Impact of diversity: Putnam’s pessimistic prognoses 3

4. Lower Prejudice Opportunity for contact + Out-group friends - Percentage of Out-groupers + Percentage of Out-groupers + Higher Threat/ Competition Higher Prejudice + Putnam’s (2007) ‘Diversity-Distrust Hypothesis’: Threat vs Opportunity 4 = ‘conflict theory’ (Putnam, 2007): “diversity fosters out-group distrust and in-group solidarity” (p. 142) “I think it is fair to say that most (though not all) empirical studies have tended instead to support conflict theory ” (Putnam, 2007, p. 142)

5. 5 5

6. “In colloquial language, people living in ethnically diverse settings appear to ‘hunker down’ – that is, to pull in like a turtle.” (Putnam, 2007, p. 149) Putnam, R. D. (2007). E Pluribus Unum: Diversity and community in the twenty-first century. The 2006 Johan Skytte Prize Lecture. Scandinavian Political Studies, 30, 137-174.

7. What is the relationship between diversity and trust? Mixed Findings  More Diversity  Less Trust  Putnam (2007); Lancee & Dronkers (2008) ; Fieldhouse & Cutts (2010)  More Diversity  More Trust  Marschall & Stolle (2004; Black sample); Fieldhouse & Cutts (2010; ethnic minority sample in UK); Morales & Echazarra (forthcoming)  More Diversity  No effect on Trust  Marschall & Stolle (2004; White sample); Gesthuizen, van der Meer & Scheepers (2008); Hooghe et al. (2008) 7

8. 8 Some Critical Issues in the Putnam Diversity Hypothesis 8  Role of disadvantage  Measures of Diversity  Index used  Level of measured diversity  Missing or inappropriate measures of intergroup contact  Putnam uses high-threshold measure of contact (friends)  Does not test whether contact mediates or moderates diversity effect

9. 9 ‘The Contact Hypothesis’ (Allport, 1954) Positive contact with a member of another group (often a negatively stereotyped group) can improve negative attitudes: -- not only towards the specific member, --but also towards the group as a whole 9

10. 10 Does Contact Work? Results of a ‘Meta–Analysis’  Number of Studies:515 studies  Dates of Studies:1940s -- 2000  Participants:250,089 people from 38 nations  Consistent, significant negative effect: more contact, less prejudice The more rigorous the research, the larger the effect (Pettigrew & Tropp, 2006, 2011) 10

11. 11 Do We Have Enough Evidence To Challenge Putnam and Impact Policy? Imagine you give evidence to the government on the relevance of your work (e.g., on improving inter- ethnic relations), armed with a data base consisting purely of studies using under-graduates. You are left … exposed! 11

12. 12 Significant Weaknesses of Prior Research on Contact Failure to study contact: (1) over time (2) at the level of the neighbourhood (3) taking account of diversity as well as deprivation (4) using multi-level analysis 12

13. (PIs: M. Hewstone, A. Heath, C. Peach, S. Spencer; Post docs: A. Al Ramiah, N. Demireva, S. Hussain, K. Schmid)  Test of integrated model of group threat theory and contact theory, to examine relationship between macro-level diversity and both individual-level and neighbourhood-level attitudinal outcomes  Sampled respondents from neighbourhoods of varying degrees of ethnic diversity  Control for additional key macro-level variable: neighbourhood deprivation 13

14. 14 Between-level neighbourhood measures 14  Percentage Non-White British (range: 1% - 84%)  Index of multiple deprivation (IMD; based on variety of indicators, e.g. income, employment, health deprivation) Analysis  Data hierarchically ordered in a two-level structure (respondents nested within neighbourhoods)  Multilevel structural equation modeling to account for both within- level and between-level variance of constructs

15. Overview of research Test of effects of diversity on:  Outgroup trust  Ingroup trust  Neighbourhood trust Test of effects of diversity on:  Outgroup trust  Ingroup trust  Neighbourhood trust Focus on key role of intergroup contact 15

16. 16 Putnam (2007) PERCEIVED THREAT TRUST DIVERSITY +– – 16 Diversity is perceived as threatening and has negative consequences for trust

17. 17 Our Research + – Prediction: Diversity will have positive indirect effects on trust INTERGROUP CONTACT PERCEIVED THREAT TRUST DIVERSITY + – – 17 Diversity offers opportunities for positive contact Positive contact reduces perceived threat

18. 18 Results: White British respondents (N = 868) Trust in neighbours Diversity (Ethnic fractionalization) Diversity (Ethnic fractionalization).55**–.34*** –.23** –.43*** Ingroup Trust Outgroup Trust Perceived Threat Intergroup Contact –.29*** –.30*** Diversity has positive indirect effects on Trust Outgroup Trust (b =.31, z = 2.93, p <.01), Ingroup Trust (b =.21, z = 2.72, p <.01), Neighbourhood Trust (b =.23, z = 2.93, p <.01) 18

19. 19 Results: Ethnic minority respondents (N = 797) Trust in neighbours Diversity (Herfindahl) Diversity (Herfindahl).30**–.38*** –.30*** Ingroup Trust Outgroup Trust Perceived Threat Intergroup Contact –.31*** –.22***.16*.17*.24**.21** 19 Diversity has positive indirect effects on Trust Outgroup Trust (b =.16, z = 2.65, p <.01), Ingroup Trust (b =.16, z = 2.60, p =.01), Neighbourhood Trust (b =.12, z = 2.42, p =.02)

20. 20 Contextual effect of intergroup contact 20 Do individuals from different contexts who have the same amount of intergroup contact differ in their intergroup attitudes? Does the context influence intergroup attitudes over and above individual level variables? If so, then context drives this difference (contextual effect) -- can’t be explained with individual level variables. Do individuals from different contexts who have the same amount of intergroup contact differ in their intergroup attitudes? Does the context influence intergroup attitudes over and above individual level variables? If so, then context drives this difference (contextual effect) -- can’t be explained with individual level variables.

21. Contextual effect of intergroup contact Direct Intergroup Contact Intergroup attitudes (i.e., prejudice) Within Group Effect (Level 1): e.g., β W = -.30 Between Group Effect (Level 2): e.g., β B = -.50 Contextual Effect: e.g., β C = β B - β W = -.20 (Extended Contact) Within Group Effect (Level 1): e.g., β W = -.30 Between Group Effect (Level 2): e.g., β B = -.50 Contextual Effect: e.g., β C = β B - β W = -.20 (Extended Contact) βWβW βBβB βCβC Context C Context B Context A 21 Do individuals from different contexts who have the same amount of intergroup contact differ in their intergroup attitudes? Then context drives this difference (contextual effect) -- can’t be explained with individual level variables.

22. Results: Leverhulme, UK data 22 Intergroup contact Ingroup Bias Individual level Context level β W = -0.346*** β B = -2.223*** Contextual Effect: β C = β B - β W = -1.877** Intergroup contact Ingroup Bias *controlled for age, sex, education, and IMD

23. Results: Leverhulme, UK data 23 Intergroup contact Ingroup Bias Individual level Context level β W = -0.346*** β B = -0.614 Contextual Effect: β C = β B - β W = -0.270 Indirect effect on context level: -0.343*** Contextual Effect: β C = β B - β W = -0.270 Indirect effect on context level: -0.343*** Intergroup contact Ingroup Bias *controlled for age, sex, education, and IMD Tolerant norms 0.892*** -1.840***

24. Results: MPI data, German longit. Data 24 Intergroup contact Ingroup Bias Individual level Context level β W = -0.031* Contextual Effect: β C = β B - β W = -0.161* Indirect effect on context level: -0.041 + Contextual Effect: β C = β B - β W = -0.161* Indirect effect on context level: -0.041 + *controlled for age, sex, education, and unemployment, and sse rate β B = -0.192** Intergroup contact Tolerant norms time 1 time 2 Threat 0.130 + -0.318*

25. 25 Putnam’s impact 25 “Will first-hand experience weaken stereotypes? That was the belief of the sociologist Samuel Stouffer, who observed during the Second World War that white soldiers who fought alongside blacks were less racially prejudiced than white soldiers who had not. The political scientist Robert Putnam has stood Stouffer, and Aristotle, on their heads. Putnam has found that first-hand experience of diversity in fact leads people to withdraw from these neighbours” (p. 5)

26. Types of intergroup contact: whether and how they work 26

27. DIRECT CONTACT  Quantity of contact – frequency of interaction with outgroup members, e.g., ‘how often do you meet/talk to/etc. outgroup members where you live/shop/socialize, etc?’  Quality of contact – nature of the interaction with outgroup members, e.g., how positive/negative; friendly/unfriendly, etc, is the contact?’  Cross-group friendship – being friends with outgroup members, e.g., ‘How many close outgroup friends?’ EXTENDED CONTACT  I ndirect/Vicarious contact, via family or friends, e.g., ‘How many of your family members/friends have outgroup friends? 27

28. Longitudinal Effects and Evidence of Mediators Direct contact: 28

29. 29

30. 3-Wave Study of Longitudinal Contact in South African ‘Coloured’ Schools (Swart, Hewstone, Christ, & Voci, JPSP, 2011)  Age (yrs):  T1: Mean (SD) = 14.68 (1.06)  T2 (+ 6 mths): Mean (SD) = 15.31 (1.03)  T3 (+ 6 mths): Mean (SD) = 15.67 (1.05)  Variables:  Predictors: cross-group (white) friends  Mediators: intergroup anxiety; empathy  Outcomes: positive outgroup attitudes; outgroup variability; negative action tendencies  3-wave cross-lagged analyses  3-waves permit mediation analyses  Time 1 ‘predictor’ -> Time 2 ‘mediator’ -> Time 3 ‘Outcome’ 30

31. 31 x 10 x 12 x9x9 Positive Outgroup Attitudes x 11 y 28 y 30 y 27 Positive Outgroup Attitudes y 29 y 10 y 12 y9y9 Positive Outgroup Attitudes y 11 x 14 x 15 x 13 Perceived outgroup Variability y 14 y 15 y 13 Perceived outgroup Variability y 32 y 33 y 31 Perceived outgroup Variability x 17 x 18 x 16 Negative Action Tendencies y 17 y 18 y 16 Negative Action Tendencies y 35 y 36 y 34 Negative Action Tendencies x1x1 x2x2 Outgroup Friendships y1y1 y2y2 Outgroup Friendships y 19 y 20 Outgroup Friendships x4x4 x5x5 x3x3 Intergroup Anxiety y4y4 y5y5 y3y3 Intergroup Anxiety y 22 y 23 y 21 Intergroup Anxiety x7x7 x8x8 x6x6 Empathy y7y7 y8y8 y6y6 y 25 y 26 y 24 Empathy

32. 32 Blue: ‘forward’; Red: ‘reverse’ Positive Outgroup Attitudes Positive Outgroup Attitudes Positive Outgroup Attitudes Perceived outgroup Variability Perceived outgroup Variability Perceived outgroup Variability Negative Action Tendencies Negative Action Tendencies Negative Action Tendencies Outgroup Friendships Outgroup Friendships Outgroup Friendships Intergroup Anxiety Intergroup Anxiety Intergroup Anxiety Empathy -.15** -.27*** -.14** -.11**.13** -.14**.23***.15**.23*** -.14** -.11**.13** -.14**.23*** -.15**.23***.15** -.27***

33. Making Sense of ‘Spaghetti’  Green paths are autoregressive.  Blue paths are 'forward' paths (as predicted by contact model).  Red paths are 'reverse' paths (self-selection).  Model equates paths from Wave 1-2, and 2-3  All paths indicated are significant. 33

34. 34 Blue: ‘forward’; Red: ‘reverse’ Positive Outgroup Attitudes Positive Outgroup Attitudes Positive Outgroup Attitudes Perceived outgroup Variability Perceived outgroup Variability Perceived outgroup Variability Negative Action Tendencies Negative Action Tendencies Negative Action Tendencies Outgroup Friendships Outgroup Friendships Outgroup Friendships Intergroup Anxiety Intergroup Anxiety Intergroup Anxiety Empathy -.15** -.27*** -.14** -.11**.13** -.14**.23***.15**.23*** -.14** -.11**.13** -.14**.23*** -.15**.23***.15** -.27***

35. 35 Blue: ‘forward’; Red: ‘reverse’ Positive Outgroup Attitudes Positive Outgroup Attitudes Positive Outgroup Attitudes Perceived outgroup Variability Perceived outgroup Variability Perceived outgroup Variability Negative Action Tendencies Negative Action Tendencies Negative Action Tendencies Outgroup Friendships Outgroup Friendships Outgroup Friendships Intergroup Anxiety Intergroup Anxiety Intergroup Anxiety Empathy -.15** -.27*** -.14** -.11**.13** -.14**.23***.15**.23***

36. The Surprising Impact of “weak ties” Extended Contact: 36

37. 37 Some of my friends have friends who are... (outgroup members)  ‘Extended contact’ is second-hand, rather than involving the participants in direct intergroup contact themselves  Just knowing other people in your group who have out-group friends might improve attitudes to the out-group (Wright et al., 1997)

38. 38

39. Number of Direct Friends Intergroup Anxiety R 2 =.21 Number of Indirect Friends General Group Variability R 2 =.11 Prejudice Towards The Group R 2 =.48 -.18***.17** -.03.53***.52 -.31*** -.21***.60*** -.22*** Extended Contact in Northern Ireland (Results for Catholics and Protestants; N = 316) (Paolini, Hewstone, Cairns & Voci, 2004).79.89

40. 40 Key facts about extended contact  It works by changing group norms  It is especially effective for those who have no direct contact  It should lead people to take up more opportunities for direct contact in the future

41. 41 Impact of Indirect Contact is Moderated by Amount of Direct (Friendship) Contact (NI- CRU Survey, N=984; Christ, Hewstone et al., PSPB, 2010) When does extended contact work best? When direct contact is low.

42. 42 Longitudinal analysis of the effects of extended contact at time 1 on direct contact at time 2 (Swart, Hewstone, Tausch et al., in prep.) Extended Contact (Time 1) Extended Contact (Time 1) Neighbourhood Contact Quantity (Time 2) Neighbourhood Contact Quantity (Time 2) Controlling for direct contact scores at Time 1 Neighbourhood Contact Quality (Time 2) Neighbourhood Contact Quality (Time 2) Contact with Friends (Time 2) Contact with Friends (Time 2).15***.23***.21***

43. An Experimental Comparison of Different Forms of Contact

44. 44 http://www.isxys.org/isolation/wp-content/uploads/2007/02/turkishpopulation1960-present.jpg Evidence from Cyprus

45. Study 1  Participants: 52 female students (26 pairs) at the University of Cyprus  Recruitment criteria:  Greek/Cypriots  Friends with each other  Good knowledge of English

46. Study 1: Methodology- Procedure T1T1 Pre- test (baseline measures) 1 WEEK T2T2 Intervention & Post- test

47.  Type of Contact – Manipulation of Direct vs Extended contact  Randomly allocate one of each pair of participants to each of the two conditions:  Direct contact: a 10 minute structured face-to-face interaction of the first member of the pair with a T/C confederate.*  Extended contact: the 2nd member of the pair observed her friend interacting with the T/C through a one-way mirror.  * the T/C confederate was trained to give the same answers every time. 47 Study 1: Methodology - Contact Intervention

48. Study 1: Results Direct Contact Mean (SD) Extended contact Mean (SD) Attitudes tow. out- group member (thermometer) 8.44 (.92)8.23 (1.31) Typicality of out-group member 2.28 (.89)2.58 (1.20) In-group (Self) disclosure 3.40 (.76)3.50 (.81) Out-group disclosure 3.36 (.57)3.38 (.75) Group Salience 1.97 (.87)2.26 (1) Contact (State) Anxiety 1.47 (.34)1.5 (.41)

49. Study 1: Attitudes Results Pre – Post Contact (improved attitudes, esp. Direct contact)

50. Impact of contact 50

51. 51 Multiple Outcomes of Intergroup Contact 51  Explicit attitudes  Attitude strength  Implicit attitudes  Neural processes  Trust  Forgiveness  Behavioural intentions  Outgroup-to-outgroup generalization: the ‘secondary transfer effect’. *

52. Are the effects of contact with members of one group restricted to that outgroup, or do they have ‘knock-on’ or ‘trickle-down’ effects on attitudes towards other groups? Schmid, K., Hewstone, M., Küpper, B., Zick, A., & Wagner, U. (2012). Social Psychology Quarterly, 75, 28–51. Are the effects of contact with members of one group restricted to that outgroup, or do they have ‘knock-on’ or ‘trickle-down’ effects on attitudes towards other groups? Schmid, K., Hewstone, M., Küpper, B., Zick, A., & Wagner, U. (2012). Social Psychology Quarterly, 75, 28–51.

53. 53 Overview  Test of secondary transfer effects in cross-national comparison  8 European countries: France, Germany, Hungary, Italy, the Netherlands, Poland, Portugal, UK  Moderation by Social dominance orientation (SDO)?  Ideology of inequality (Pratto, Sidanius et al., 1994)  Data from GFE Europe survey (30-minute cross- sectional CATI survey)

54. Full sample analysis (N = 7042; Schmid, Hewstone et al., 2012; controls: age, gender, education, income, political orientation ) Intergroup Contact – Immigrants Negative Attitudes – Immigrants Negative Attitudes – Immigrants Attitudes Jewish Negative attitudes – homosexuals Negative attitudes – homosexuals –.13*** –.15***.39***.37*** Low SDO: –.22*** High SDO: –.08 ns Low SDO: –.22*** High SDO: –.08 ns Overall mediation: b = –.06, z = –6.68*** Moderated mediation: Low SDO: b = –.08, z = –6.65*** High SDO: b = –.02, z = –3.14*** Overall mediation: b = –.06, z = –6.68*** Moderated mediation: Low SDO: b = –.08, z = –6.65*** High SDO: b = –.02, z = –3.14***

55. 55

56. 1.76 * Longitudinal Secondary transfer effect in Northern Ireland (N = 181 Catholics, 223 Protestants; matched at T1-T2, 1 year; Tausch et al.,2010).43 *** 1.84 * * p <.05; ** p <.01; *** p <.001 1.07, n.s. Attitude to racial minorities T2 Attitude to racial minorities T2 Ingroup feeling thermometer T2 Ingroup feeling thermometer T2 Attitude to ethno-religious outgroup T2 Attitude to ethno-religious outgroup T2 Neighbourhood contact with ethno-religious outgroup T1 Neighbourhood contact with ethno-religious outgroup T1 Controlling for: Contact with and attitude to racial minorities T1 Controlling for: Contact with and attitude to racial minorities T1 Attitude to ethno-religious outgroup T1 Attitude to ethno-religious outgroup T1 56

57. Kronenberg & Hewstone (in prep.) Does contact impact behaviour, and when it really matters?Archival re-analysis of contact effects in extreme conditions: Rescuers of Jews from Nazi Europe 57

58. 58 Data  Data from the Altruistic Personality and Prosocial Behaviour Institute (Oliner/Oliner 1988)  510 respondents from 15 European countries  Collected in the 1980s  Retrospective case-control sample: Case sample of identified rescuers (N=346, recognized by Yad Vashem, The Holocaust Martyrs’ and Heroes’ Remembrance Authority, as ‘Righteous among the Nations’) Control sample matched on age, sex, education, region (N=164) Final sample 412 respondents (297 rescuers, 115 non- rescuers)

59. 59 Main Hypothesis (with multiple controls, e.g. for opportunities to help; pro-social orientation) 59  Pre-war friendships with Jews increase the probability of rescuing Jews (especially Jewish friends) (direct contact via friends)

60. Multinomial logistic regression (variables coded [0,1]): Pre-war frnds. w Jews Helping Jewish friends 12.19** Helping other Jews 2.24** Notes: N = 412. Coefficients are odds ratios. No control variables. + p < 0.10, * p < 0.05, ** p < 0.01. 3. Empirical Application The Impact of Pre-war Friendships with Jews

61. 61 Odds Ratio  Odds ratio (OR) calculated shows the probability of helping (Jewish friends; other Jews) vs not-helping  OR of 12.19 in previous table 1 means:  The odds of helping other Jews vs. not helping increase (only) by a factor of 2.24 if respondents had Jewish friends before the war.  Less technically: If you had pre-war Jewish friends, the probability of Helping Jewish Friends divided by the probability of not-Helping was 12.19 times higher than if you did not have pre- war Jewish friends. Having Jewish friends before the war made potential rescuers more likely to help, especially to help Jewish friends, but also to help other Jews.

62. Pre-war frnds. w Jews Age Prosocial orientation Command zone Size Jewish population Number of rooms Many neighbours Helping Jewish friends 15.41** 1.07** 18.43** 10.89** 0.98 15.28** 0.86 Helping other Jews 2.89** 1.05* 5.18* 10.36** 1.19** 12.11** 0.39* Multinomial logistic regression (variables coded [0,1]): Notes: N = 412. Coefficients are odds ratios. Additional control variables: gender; education level; religiosity; religious confession; SS zone, Jewish Neighbours, partner/children in household, financial resources. + p < 0.10, * p < 0.05, ** p < 0.01. 3. Empirical Application The Impact of Pre-war Friendships with Jews: Effect of adding controls

63. Is everything for the best in this best of all possible worlds? Limits to the impact of contact: Segregation, de- segregation, and re-segregation Observational research:

64. 64 Cafeteria study in mixed school 64  Coded who sat where and with whom in cafeteria of a 6th Form College (16-18 yrs) in NW England  (40% ethnic minority, mostly Pakistani- and Bangladeshi-heritage British Asians)

65. Area A1 Costa Food service counters Area A3 Pizza counter Area A4 Area A2 DOO R Kitchen Day 1 Time 1 Occupied seats 89 Mixed tables 1

66. 66 Coding and measures Over a two day period, 3,037 seating positions were coded; we analysed the data using:  the segregation index of dissimilarity (D; Clack et al., 2005)  Ethnic composition of ‘social units’  Side-by-side and face-to-face cross-race adjacencies (Campbell et al., 1966)  Aggregation Index of ethnic clustering (I; difference between actual vs. expected frequency with which Whites and Asians sat opposite each other; Campbell et al., 1966)

67. Asian* White* Black Other Pillar (i.e., not a seat) Empty seat

68. 68 Coded data of 22 time intervals...

69. Area A1 Costa Food service counters Area A3 Pizza counter Area A4 Area A2 DOO R Kitchen Day 1 Time 1 Occupied seats 89 Mixed tables 1

70. Area A1 Costa Food service counters Area A3 Pizza counter Area A4 Area A2 DOO R Kitchen Day 1 Time 2 Occupied seats 189 Mixed tables 5

71. Area A1 Costa Food service counters Area A3 Pizza counter Area A4 Area A2 DOO R Kitchen Day 1 Time 6 Occupied seats 295 Mixed tables 11

72. 72 All White All Asian White/ Asian White/ Asian/ Black/ Other White/ Black/ Other Asian/ Black/ Other Black / Other % of social units 58.97%30.91%4.18%0.33%4.73%0.55%0.33% Ethnic composition of social units

73. 73 DayAreaNo. of Intervals I Upper LimitLower Limit 1110-1.99-0.98-4.36 1210-0.710-2.57 1310-0.290-1.48 1410-1.090-3.04 2112-1.6-0.32-3.82 2212-0.390-1.52 2312-0.440-3.44 2412-1.190-3.02 Note: I denotes aggregation index (negative values indicate more ethnic clustering/less cross-ethnic mixing than expected from random distribution). See Area 1... Mean Ethnic Aggregation Indices for each area across both days

74. Area A1 Costa Food service counters Area A3 Pizza counter Area A4 Area A2 DOO R Kitchen Day 2 Time 7 Occupied seats 142 Mixed tables 4

75. 75 DayAreaNo. of intervalsNumber of WhitesNumber of Asians 1110251366 121025416 13101419 141028246 2112241461 221227816 231218213 241238136 The number of Whites versus Asians in each area for both days

76. 76 Lessons from cafeteria study 76  Mixed student body does not equate with intergroup contact  Students do, in fact, report contact, including outgroup friends, and contact is associated with more positive attitudes  But why do students choose to sit apart at lunch? Does it even matter that they do?  Ongoing research

77. 77 Actual contact is crucial for integration Just ‘living together’ is not enough (re-segregation problem in cafeteria) Contact does mediate impact of neighbourhood diversity; Putnam is too pessimistic Direct and extended and forms of contact have effects Contact has multiple outcomes; STE especially important Effects of contact shown via multi-method approach: Surveys (cross-sect’l. &longitud.); experiments; archival analysis To understand diversity effects you have to study contact. Conclusions 77

78. Funding Leverhulme Trust Community Relations Unit (N.I.) Economic and Social Research Council Nuffield Foundation Russell Sage Foundation, U.S.A. Templeton Foundation, U.S.A. 78 (ex) Graduate students Maria Ioannou Dr Ananthi al-Ramiah Dr Hermann Swart Dr Nicole Tausch Dr Rhiannon Turner Dr Christiana Vonofakou Research collaborators Prof. Ed Cairns (University of Ulster) Dr Oliver Christ (University of Marburg, Germany) Prof. Joanne Hughes (University of Ulster) Dr Jared Kenworthy (University of Texas) Prof. Clemens Kronenberg (University of Mannheim) Dr Katharina Schmid (University of Oxford) Dr Alberto Voci (University of Padua, Italy) Undergraduate students Eleanor Baker Christina Floe Caroline Povah Elisabeth Reed Anna Westlake

79. 79