This presentation was used at the Brown Bag Lunch at the Netherlands Interdisciplinary Demographic Institute (NIDI) at The Hague, and at the Sociology Colloquium at Tilburg University to update scholars about the upcoming data release of the European Values Study 2017, of which the Netherlands is part of.

1. Tim Reeskens | NIDI | November 7, 2018
European Values Study:
Past, Present & Futures

2. • EVS 2017 data release is looming around the corner
• Getting updated about the past, present and future of EVS
• A brief history of the EVS
• 2017 Dutch data collection
• Data cleaning and data release
• First findings based on 2017 Dutch data
• Impact PhD-project
Intake of Presentation
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3. • It all started with these two Founding Fathers
A Brief History of the European Values Study
Ruud de Moor Jan Kerkhofs
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4. • What kind of value pattern exists in Europe?
• Is Europe a cultural unity?
• Do Christian values continue to
permeate European life and culture?
• Is a coherent alternative meaning
system replacing that of Christianity?
• What are the implications for European unity?
Why This Study?
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5. • Explorative studies
• In-depth interviews
• Group discussions
• Archive search
• Pilots
• Final survey in 1981
• Interviews based on random samples; N ≥ 1,000; 18+
• Identical (translated) questionnaires
• Coordination: Gallup London
EVS Project Design
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6. EVS Questionnaire
religion morality politics
society
family
education work leisure
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7. A Growing Project
• Almost 40 years of values research
• A growing number of countries
• Impressive scope of the study
• Highest methodological standards
• Data freely accessible (GESIS)
• Growing integration with WVS
• Overlap of 60% of questionnaire
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8. • Getting this project going: funding
• Netherlands Organization for Scientific Research (NWO)
• Tilburg School for Social and Behavioral Sciences (TSB)
• European Values Study Foundation (EVS)
• Dealing with constraints: going for mixed methods
• Sample size: 1236 (vs. 1200 respondents)
• Working towards the 1 September 2017 deadline
• Translating questionnaire
• Getting classifications right
• Instructing interviewers
The EVS 2017 in the Netherlands
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9. 911/07/2018NIDI - Brown Bag Seminar
• Fieldwork organization: I&O Research
• Sample drawn by Statistics Netherlands (CBS): 1000 + 250 + 250
• Emphasis on realized sample, more than on response rate
• Aiming at approx. 600 respondents
• Long process: 31 August 2017 to 1 March 2018
• Both reserve batches used
• Realized sample: 686 respondents (response rate close to 50 percent)
• Weights calculated by CBS, no ‘exotic’ coefficients
Method 1: Face-to-Face (CAPI)

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• Fieldwork organization: CentERdata
• Aiming at 2000 respondents
Method 2: Online (CAWI) (1)
Core Block A Block B Block C Block D
Group 1 X X X
Group 2 X X X
Group 3 X X X
Group 4 X X X
Group 5 X X X
Group 6 X X X

11. 1111/07/2018NIDI - Brown Bag Seminar
• Fieldwork: 11 September 2017 to 31 October 2017
• Response: 2034 respondents (out of 2515 ~ 80.9%)
• Additional funding: completing the matrix (January 2019)
• Leveraging the panel structure: Cambridge Analytica & GDPR
Method 2: Online (CAWI) (2)
Core Block A Block B Block C Block D
Group 1 X X X + +
Group 2 X X + X +
Group 3 X X + + X
Group 4 X + X X +
Group 5 X + X + X
Group 6 X + + X X

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• How to analyze the Mixed Method data?
• Finding a harmonized strategy (with CH, DE, FI & IS)
• Multiple imputation (?)
• Using block dummies on completed interviews (?)
• Dealing with attrition
• First things first: having the data available
Current Challenges

13. After the Dutch Data Collection
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From Data Collection to Data Release
ODS
MDS1
MDS2a
MDS2b
IDS
Raw dataset
Integrated dataset
Harmonized
dataset
Anonymized
dataset
Modified dataset
Central teams
National teams
Public release

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National Team: From ODS to MDS1
ODS
MDS1
MDS2a
MDS2b
IDS
1.Save (un-edited) ODS for preservation
2.Check and edit ODS
3.Standardise edited ODS
4.Upload results to myEVS
Country-specific syntax file

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Central Team: From MDS1 to IDS
ODS
MDS1
MDS2a
MDS2b
IDS
1. Deposit and Ingest check
2. Data processing
3. Data harmonization
4. Data anonymization
5. Generate IDS

17. Harmonization through SERISS
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18. • Horizon 2020 project
• Involving major European survey infrastructures
• ESS, EVS, SHARE, GGP, CESSDA, WAGEINDICATOR
• Aims
• Addressing key challenges for cross-national data collection
• Breaking down barriers between social science infrastructures
• Embracing the future of the social sciences
• Impact on data collection, harmonization, cleaning and dissemination
Synergies for Europe’s Infrastructure in Social Sciences
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19. Educational cleavage in social attitudes
• Next to debates in society, much scholarly attention
• Dutch books edited by De Lange et al (2015) and
Van der Werfhorst (2015); SCP reports
• Bovens & Wille (2011): Diploma Democracy
• Inglehart & Norris (2017): Winners and losers of globalization
Has there been a polarization of social attitudes
between higher and lower educated individuals
in the Netherlands, with respect to relevant social
and political values and attitudes?
Ahead of Data Release: First Project
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20. • EVS waves: 1999, 2008 and 2017 for the Netherlands
• Survey data: Face-to-face interviews (all waves)
• Increasing educational gaps:
• Lower educated: Primary and lower secondary (33.2 percent)
• Middle educated: Higher secondary education (33.5 percent)
• Higher educated: Tertiary education (33.3 percent)
• ANCOVA ~ analysis of covariance
Year (1999, 2008, 2017), Education (lower, middle, higher),
Interaction between year and education
• F-tests to test the significance of each main and interaction effect
Analytical Strategy
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• If you had to choose, which one of the things on this card would you say
is most important? [And which would be the next most important?]
A. Maintaining order in the nation
B. Giving people more say in important government decisions
C. Fighting rising prices
D. Protecting freedom of speech
Postmaterialism (1)

22. Postmaterialism (2)
Year: F(2) = 2.711; p = 0.067
Education: F(2) = 37.376; p < 0.001
Year * Education: F(4) = 1.541; p = 0.188
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• How often do you pray outside of religious services?
1 = never
2 = less often
3 = several times a year
4 = at least once a month
5 = once a week
6 = more than once a week
7 = every day
Religiosity (1)

24. Religiosity (2)
Year: F(2) = 5.424; p = 0.004
Education: F(2) = 83.043; p < 0.001
Year * Education: F(4) = 1.196; p = 0.310
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• Please tell me for each of the following whether you think it can always
be justified, never be justified, or something in between
Claiming state benefits which you are not entitled to | Cheating on tax if
you have the chance | Avoid a fare on public transport | Taking the drugs
marijuana or hashish | Someone accepting a bribe in the course of their
duties | Homosexuality | Abortion | Divorce | Euthanasia | Suicide
1 = never – 10 = always
Moral Permissiveness (1)

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Moral Permissiveness (2)
Year: F(2) = 51.387; p < 0.001
Education: F(2) = 152.157; p < 0.001
Year * Education: F(4) = 1.243; p = 0.290

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• A job is alright but what most women really want is a home and children
1 = agree strongly | 2 = agree | 3 = disagree | 4 = disagree strongly
Gender Equality (1)

28. Gender Equality (2)
Year: F(2) = 22.871; p < 0.001
Education: F(2) = 184.165; p < 0.001
Year * Education: F(4) = 1.787; p = 0.129
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• On this list are various groups of people. Could you identify any that you
would not like to have as neighbors?
People of a different race | Muslims | Immigrants/Foreign workers |
Drug addicts | Homosexuals | Jews
Intolerance: Identify at least one of the three highlighted in green
Intolerance (1)

30. Intolerance (2)
Year: F(2) = 26.185; p < 0.001
Education: F(2) = 43.710; p < 0.001
Year * Education: F(4) = 1.038; p = 0.386
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31. 3111/07/2018NIDI - Brown Bag Seminar
• Tell me, for each item listed below, how much confidence you have in
them, is it a great deal, quite a lot, not very much or none at all?
The church | The armed forces | The education system | The press |
Trade unions | The police | Parliament | Civil service | The social security
system | The European Union | The justice system
1 = None at all | 2 = Not very much | 3 = Quite a lot | 4 = A great deal
Political Trust (1)

32. Political Trust (2)
Year: F(2) = 19.652; p < 0.001
Education: F(2) = 67.975; p < 0.001
Year * Education: F(4) = 8.286; p < 0.001
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33. • First exploration looks promising
• Worlds apart? Yes!
• Growing worlds apart (polarization)? No!
• Particularly something going on with political trust
• Evidently, more research needed!
• Not only between groups, also within groups (polarization)
Tentative Results
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34. Should we Talk of a Full Educational Divide? (1)
1. Structural differences
• Segmentation (substantial groups)
• Segregation
• Social (friends/partner)
• Geographical (cities/neighborhoods)
• Stratification
• Wealth (income)
• Well-being (health)
2. Attitudinal differences
• Norms and values
• Religion
• Political attitudes
Deegan-Krause (2007)
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35. Should we Talk of a Full Educational Divide? (1)
3. Institutional differences
• Societal participation
• Organizations
4. Identity
• Meritocracy
• Higher educated: More identification
• “Proof of inability” (Bovens et al., 2014)
• Calimero complex (Van Heest, 2018)
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Bovens, Dekker & Tiemeijer (2014)

36. • Cultural Capital? (Bourdieu, 1977)
• Embodied (personality, speech, skills)
• Objectified (clothes, belongings)
• Institutionalized (education, specialized knowledge)
• “The extent to which people value, demonstrate, and master the lifestyle
of the cultural elite” (Van der Waal & De Koster, 2015)
• How to measure CC?
• Parental education?
• Linguistic competence?
• Cultural knowledge and activities?
• Within-group differences (e.g. gender, ethnicity)
And What Are the Underlying Mechanisms?
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37. • Political trust
• Populism (democratic or not?)
• “Democracy = tyranny of majority vote”
(Nieuwelink, Ten Dam & Dekker, 2018)
• Particularly higher educated
• Less emphasis on equality, justice,
minority groups
The End of Our Liberal Democracy?
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38. So, to Conclude
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