individual, country and societal cluster differences on measures of personality, attitudes, values,...

Learning and Individual Differences xxx (2010) xxx–xxx

LEAIND-00432; No of Pages 12

Contents lists available at ScienceDirect

Learning and Individual Differences

j ourna l homepage: www.e lsev ie r.com/ locate / l ind i f

Individual, country and societal cluster differences on measures of personality,attitudes, values, and social norms☆

Lazar StankovNational Institute of Education, 1 Nanyang Walk, 637616 Singapore

☆ The work reported in this paper was carried out whthe Educational Testing Service (ETS), Princeton, New Jerthis paper are those of the author, not of the ETS. Thissponsored by the Air Force Research Laboratory, under a1-0375. The U.S. Government is authorized to reproduGovernmental purposes notwithstanding any copyrighand conclusions contained herein are those of the authoras necessarily representing the official policies or endoimplied, of the Air Force Research Laboratory or the U.S

E-mail address: [email protected].

1041-6080/$ – see front matter © 2010 Elsevier Inc. Aldoi:10.1016/j.lindif.2010.09.002

Please cite this article as: Stankov, L., Indivsocial norms, Learning and Individual Differ

a b s t r a c t
a r t i c l e i n f o
Article history:Received 27 December 2009Received in revised form 1 September 2010Accepted 6 September 2010Available online xxxx

Keywords:Cross-cultural differencesPersonalitySocial normsSocial attitudesHLM analysis

This study investigated cross-cultural differences on 38 subscales from 4 major domains—personality, socialattitudes, values, and social norms. These scales were administered to participants who took the Test ofEnglish as a Foreign Language™ (TOEFL®, N=1,600) and U.S. college students (N=429). Total variability ofeach subscale was split into individual, country (45), and societal cluster (9 world regions) components usinghierarchical linear modeling procedures. Individual variability accounted for between 67.69% and 96.43%, andcountry and societal clusters accounted for, on average, 11% of the total variance. Furthermore, cross-culturaleffects attributable to country and societal clusters were less pronounced on measures of personality andvalues than they were on measures of social attitudes and social norms. A composite representing theconservatism dimension showed pronounced cultural differences (25% of total variance), and the pattern ofmeans revealed that Europeans hold more liberal attitudes, values, and beliefs than people from other worldregions.

ile the author was employed atsey. The opinions expressed inmaterial is based on researchgreement number FA9550-04-ce and distribute reprints fort notation thereon. The viewsand should not be interpretedrsements, either expressed or. Government.

l rights reserved.

idual, country and societal cluster differencesences (2010), doi:10.1016/j.lindif.2010.09.002

© 2010 Elsevier Inc. All rights reserved.

Cross-cultural psychologists are interested in finding out howmuch of the variance in measures of a particular construct, sayConscientiousness, is related to interindividual differences, and howmuch is attributable to cultural differences (see Smith, Bond, &Kagitcibasi, 2006). If cultural (e.g., between-countries) differences aresignificant relative to individual differences, one can explore thepattern of these differences and search for their causes. This process,largely inspired by the logic of statistical inference like that embodiedin the analysis of variance (ANOVA) procedure, has been successful inarriving at a set of constructs that are particularly sensitive to cross-cultural influences. This study focuses on constructs and measuresfrom four broad domains—personality, social attitudes, values, andsocial norms—that have survived a significant amount of scrutiny andare known to show cross-cultural differences.

Unfortunately, cross-cultural psychologists have paid little atten-tion to the next logical step that compares two or more psychologicalconstructs in terms of the breakdown of the total variance intoindividual and cultural components. Thus, they rarely ask whether

cross-cultural differences in personality traits are smaller or greaterthan cross-cultural differences in, say, social attitudes or social norms.

The reason why little attention has been paid to the comparisonsof different psychological constructs in terms of their variancecomponents may be due, in part, to the absence of appropriatemethodological tools. These comparisons can be conducted, however,using models-based regression analyses such as hierarchical linearmodeling (HLM, see Raudenbush & Bryk, 2002), which have beendeveloped more recently. HLM has at least two features that make ituseful for analyzing cross-cultural data. First, it can easily deal withdata from studies that involve many rather than just a few countries.Second, it can handle nested variables involving two or three levels sothat the amount of variance related to, say, individuals withincountries and countries within world regions can be calculated.

The remainder of this introductory section consists of two parts.The first part is devoted to substantive issues related to the fourpsychological domains and measures used to assess differentconstructs in the present study. Of particular importance in ourprevious work is the conservatism dimension (see Stankov, 2009). Inthe second part, the main features of the HLM procedures areelaborated in more detail.

1. Culture from the psychological perspective

In psychology, the term culture refers to an accumulated set ofshared beliefs, values, and social norms which impact the behavior ofa relatively large group of people (cf. Lustig & Koester, 2003). Thepresent study was designed with a view that psychological studies of

on measures of personality, attitudes, values, and

http://dx.doi.org/10.1016/j.lindif.2010.09.002

mailto:[email protected]


http://www.sciencedirect.com/science/journal/10416080


2 As pointed out by an unknown reviewer, both countries and world regions (orsocietal clusters according to House et al., 2004) may be seen as representinggeographic or political, not necessarily cultural regions. This is an important point thatcalls for further elaboration. Most countries are indeed geographic/political structuresand using them as units in cross-cultural studies may be open to criticism of the kindimplied by the reviewer's comments. World regions, however, are somewhat differentand the claim is true only in part. Classification into world regions is based on clusteranalyses of measures of psychological constructs, not on geographic or politicalconsiderations, but the unit of analysis is still country, not the individual. Perhapsbecause of this difference in the procedures used for classification, one can expect toobtain more pronounced role of world regions in the overall variability for most

2 L. Stankov / Learning and Individual Differences xxx (2010) xxx–xxx

culture should include measures from a broad range of constructs. Atone end are measures of personality traits that are traditionally seenas being private and unique to the individual. Cultural differences inpersonality traits may be related to social influences or, alternatively,assuming a strong biological basis, different patterns of these traitsmight have evolved in different societies. At the other end aremeasures designed to assess how a person perceives implicit andexplicit rules and regulations (social norms, for short) that aresupposedly the same for everybodywithin a society. In between thesetwo endpoints there are many other psychological constructs, twocategories of which (social attitudes and values) are included in thepresent study.

Brief definitions of the four domains relevant to our discussion ofculture are as follows:

• Personality is a collection of emotion, thought, and behavior patternsunique to a person. These patterns are captured by statements thatdescribe the way we “think, feel or act.”

• Social attitudes are states of mind, and/or feelings towards a specificobject or social interaction. They are captured by statements thatelicit the expression of beliefs about what is true, real, or good insocial situations (cf. Saucier, 2004).

• Values are guiding principles and/or standards about some desirableend-state of existence (Rokeach, 1973; see also Schwartz, 2003).They are criteria people use to evaluate others, themselves, actions,and events.

• Social norms represent a set of beliefs (or perceptions) about theexpected standards of behavior that are sanctioned and enforced,sometimes implicitly, by a society.

These are all psychological aspects of culture that have receivedattention recently. Conceptually, these four domains differ from eachother. In general, empirical studies have supported this claim, eventhough in a number of recent studies noteworthy correlationsbetween constructs from the four domains have been reported(Hofstede, 2001; House, Hanges, Javidan, Dorfman, & Gupta, 2004;Inglehart, Basañez, & Moreno, 1998; Inglehart & Carballo, 1997;International Social Survey Program, 1997; Leung & Bond, 2004;Leung et al., 2002; McCrae, 2002; McCrae & Allik, 2002; McCrae,Terracciano, & 79 members of the Personality Profiles of CulturesProject, 2005; Roccas, Sagiv, Schwartz, & Knafo, 2002; Schmitt, Allik,McCrae, & Benet-Martinez, 2007; Schwartz & Bardi, 2001; Stankov &Knezevic, 2005). These domains provide context for the expression ofpeople's competencies and therefore for life success (see Sternberg &Grigorenko, 2004). They also have the potential for improvingunderstanding of the causes of social friction.

It is essential to keep in mind the fact that empirical evidenceindicates that each domain is multidimensional. For example, in thisstudy there are 10 (Big Five plus additional 5)well-defined personalitytraits, 6 social attitudes dimensions, 9 dimensions of social norms, andsome 11 value systems.1 Altogether, there are 38 different constructs/scales employed in this study. To avoid clutter, they are listed andbriefly described in Table 1. Examples of statements from each scaleare provided in the Method section.

1.1. Conservatism: an important dimension of cross-cultural differences

The data from the present study can also be used to examine cross-cultural differences on the psychological dimension of conservatismwhich captures specific aspects of the four domains listed previously(see Stankov, 2009). Stankov (2007) reported the outcome of factoranalysis of the same set of variables as those listed in Table 1. Theparticipants were community college students within the United

1 Scales that form Schwartz' Values Survey are based on the circumplex model, notfactor analysis, and I use the term value system instead of dimensions to indicate thisconceptual distinction.

Please cite this article as: Stankov, L., Individual, country and societal csocial norms, Learning and Individual Differences (2010), doi:10.1016/j.l

States. In the Stankov (2007) study, a well-defined factor ofconservatism was identified (see also Stankov & Lee, 2008, 2009). Inthe present study, a composite score for conservatism will becalculated and used in the HLM analyses. Stankov (2009) pointedout that the conservatism dimension is of particular importance sinceit correlates at both individual and countries' levels with cognitiveperformance.

1.2. Assessing the effects of culture

To examine the effects of culture, this study employed the HLMprogram (see Raudenbush & Bryk, 2002), which was developed forthe analyses of behavioral/social data that possess a nested structure.In the analyses reported here, individuals (Level 1) are nested withincountries (Level 2), and countries are nested within societal clusters(Level 3). Societal clusters refer to the classification of countries of theworld into broad groupings. In this work we used the classificationproposed in the GLOBE study (see House et al., 2004) that divides theworld into 10 main geographical/cultural regions or clusters (seeTable 2).2 One of these clusters, Nordic Europe, was not included inthe present study because only five people from this region took theTest of English as a Foreign Language™ (TOEFL®) that provided thesource for our recruitment of participants.

The first aim of the current study is to assess the relativecontributions of the three nested levels to the overall variability ofeach of the 38 measures. The focus is on two topics. First, variancecomponents of the measures from each of the four domains arepartitioned. In psychological research, the largest amount of varianceis usually related to variability among individuals. A low percentage ofvariance accounted for by Level 2 and Level 3 implies that cross-cultural effects have a small role to play in the overall variability on agiven trait. On the other hand, a high percentage of varianceaccounted for by Level 2 and Level 3 implies that culture has animportant role to play. On the basis of previous work, pronouncedeffects are expected for both levels of culture (countries and worldregions) on measures employed in this study.

Much of the work in cross-cultural psychology employs countries,not societal clusters, as units of analysis. Nevertheless, some of theimportant work points to the usefulness of classifying countries intoworld regions (see House et al., 2004; Inglehart et al., 1998). Althoughthe information on each country is available, the number of peoplefrom some of the countries may be too small for meaningfulcomparisons; findings about societal clusters are likely to be morestable. Additionally, relative contributions of countries and societalclusters will be compared to the total variance of each variable. In thepresent paper, the focus is on global comparisons at the level of bothcountries and societal clusters, particularly the latter.

The second aim of the study is to compare variance decomposi-tions across different measures. These comparisons can be within andbetween the domains. It is difficult to formulate strong hypothesesregarding the variance components within a particular domain. For

measures. This is indeed one of the findings of the present study. I wish to add that ourstudies that are currently under way will use individuals rather than countries as unitsof analysis to form clusters that can, perhaps, lead to the development of apsychological atlas of the world.

luster differences on measures of personality, attitudes, values, andindif.2010.09.002


Table 1Constructs within the domains of cultural differences: personality, social attitudes, values, and social norms.

Big Five personality traitsa

1. Extraversion (vs. introversion; outgoing and physical-stimulation oriented vs. quiet and physical-stimulation averse)2. Agreeableness (affable, friendly, conciliatory vs. aggressive, dominant, disagreeable)3. Conscientiousness (dutiful, planful, and orderly vs. spontaneous, flexible, and unreliable)4. Neuroticism (vs. emotional stability: emotionally reactive, prone to negative emotions vs. calm, unperturbable, optimistic),5. Openness (open to new ideas and change vs. traditional and staid)

Additional personality traitsb

6. Belligerence (hostility and warlike attitudes towards others)7. Conservatism (tendency to resist change and maintain existing social order)8. Distrust (doubt in people's honesty)9. Achievement-seeking10. Risk avoidance

Social attitudes (Stankov/Knezevic)c

11. Toughness (machoism, hard realism, street wiseness, and Machiavellianism)12. Maliciousness (poor impulse control, sadism, resentment, and brutality)

Social attitudes (Saucier)d

13. Alphaisms (Reflects the degree to which an individual subscribes to conventional religious beliefs.)14. Betaisms (Reflects the degree to which an individual subscribes to various justifications of self-interest.)15. Gammaisms (Reflects the degree to which an individual subscribes to governmental philosophies, such as patriotism, constitutionalism, humanism, existentialism,

neoliberalism, and functionalism.)16. Deltaisms (Reflects the degree to which an individual subscribes to subjective experiences, including paranormal experiences.)17. Government interventionism18. Harshness to outsiders

Values (Schwartz)e

19. Power (authority, wealth, social power, public image, and social recognition)20. Achievement (ambition, success, capability, influence, and intelligence)21. Hedonism (pleasure, enjoyment of life)22. Stimulation (variety, excitement)23. Self-direction (creativity, freedom, independence, curiosity, and choosing own goals)24. Universalism (broadmindedness, social justice, equality, world at peace, unity with nature, wisdom, and protection of the environment)25. Benevolence (helpfulness, loyalty, forgiveness, honesty, responsibility, truth, friendship, and mature love)26. Traditionalism (respect for tradition, humility, devoutness, acceptance of one's portion in life, and moderation)27. Conformity (obedience, self-discipline, politeness, honoring parents and elders)28. Security (social order, family security, national security, reciprocation of favors, cleanliness, sense of belonging, and health)29. Spirituality (spirituality, meaning of life, sense of inner harmony, and sense of detachment)

Social norms (GLOBE)f

30.Uncertainty avoidance (the extent towhichmembers of anorganizationor society strive to avoiduncertainty by relyingonestablished social norms, rituals, andbureaucratic practices)31. Future orientation (the degree to which individuals in organizations or societies engage in future-oriented behaviors such as planning, investing in the future, and delaying

individual or collective gratification)32. Power distance (the degree to which members of an organization or society expect and agree that power should be stratified and concentrated at higher levels of an

organization or government)33. Collectivism I, Institutional Collectivism (the degree to which organizational and societal institutional practices encourage and reward collective distribution of resources and

collective action)34. Humane Orientation (the degree to which individuals in organizations or societies encourage and reward individuals for being fair, altruistic, friendly, generous, caring, and

kind to each other)35. Performance Orientation (the degree to which an organization or society encourages and rewards group members for performance improvement and excellence)36. Collectivism II, In-Group Collectivism (the degree to which individuals express pride, loyalty, and cohesiveness in their organizations or families)37. Gender Egalitarianism (the degree to which society minimizes gender role differences while promoting gender equality)38. Assertiveness (the degree to which individuals in organizations or societies are assertive, confrontational, and aggressive in social relationships)

Note. Examples for each scale are provided in the Method section of this paper.a See Saucier & Goldberg, 2002. The scales were downloaded from IPIP (n.d.).b These are based on the work of Tellegen and his colleagues (see Patrick et al., 2002). The scales were downloaded from IPIP (2008).c See Stankov & Knezevic, 2005.d Saucier, 2000.e Schwartz & Bardi, 2001.f See House et al., 2004.

3L. Stankov / Learning and Individual Differences xxx (2010) xxx–xxx

example, there is no a priori reason to expect that cultural effects areless pronounced on measures of, say, extraversion than they are onmeasures of, say, openness. For this reason, it is best to treat thepresent study as an exploratory study that seeks to identify thewithin-domain cross-cultural differences. However, comparisonsbetween the domains are possible and one expectation is that cross-cultural (i.e., combined country and societal clusters) differences onpersonality traits will be smaller than cross-cultural differences onsocial norms, with social attitudes and values falling somewhere inbetween. This is because in theory, personality traits, being char-acteristics of individuals, should show smaller cross-cultural differ-


ences than measures of social norms, which are individuals'perceptions of (or beliefs about) behaviors that are encouraged bythe society they live in. This is in the spirit of Church's (2000)framework in which heritable traits are postulated as person variablesand the broad dimensions of individualism/collectivism and self-construal are culture variables. Assuming that there will indeed be asignificant portion of each variable that can be attributed to culturaldifferences, the next step is to examine the pattern of meandifferences and identify societal clusters that stand out and differfrom other societies on these measures. These comparisons areundertaken in the last section of the present paper.



Table 2The number of participants in countries and societal clusters.

GLOBE society clusters N (%)

1. Latin Europe[France (110); Italy (47); Spain (21)]

178 9.04

2. Germanic Europe[Austria (40); Germany (111); Switzerland (10)]

161 8.17

3. Eastern Europe[Albania (20); Cyprus (20); Greece (9); Poland (47);Romania (33); Russia (43); Serbia (6)];

178 9.04

4. Latin America[Argentina (28); Bolivia (10); Brazil (40); Chile (5);Colombia (29); Costa Rica (27); Ecuador (36);El Salvador (18); Mexico (45); Venezuela (6)]

244 12.39

5. Sub-Saharan Africa[Ethiopia (22); Nigeria (60); Zambia (6)]

88 4.47

6. Middle East[Egypt (8); Morocco (13); Palestine (12);Qatar (14); Turkey (28); Yemen (7)]

82 4.16

7. Southern Asia[India (148); Indonesia (27); Malaysia (28);Philippines (33); Sri Lanka (including Sinhalese, 67);Thailand (59); Vietnam (8)]

370 18.78

8. Confucian Asia[China (124); Japan (53); Korea (18);South Korea (6); Taiwan (33)]

234 11.88

9. Anglo[United States (435)]

435 22.01

Total: 1,968 1,968Number of countries: 45

Note. Number in parentheses indicates the number of participants from a country.

3 In some of the HLM analyses, participants who declared themselves to beSinhalese were also kept as separate group from those who labeled themselves as SriLankans.

Table 3Descriptive statistics for all measures.

Measures (Total N=2029) N Nitems M SD Cronbach's alpha

Big 5 personality traitsa

(5-points Likert Scale)1. Extraversion 2021 10 3.21 0.65 .812. Agreeableness 2021 10 3.81 0.52 .753. Conscientiousness 2021 10 3.49 0.57 .754. Neuroticismb 2021 10 3.10 0.66 .815. Openness 2021 10 3.68 0.56 .78

Additional personality traits a

(5-points Likert Scale)6. Belligerence 1311 10 2.52 0.53 .647. Conservatism 1311 10 2.92 0.53 .608. Distrust 1311 10 2.63 0.49 .689. Achievement-seeking 1311 10 3.62 0.56 .7710. Risk avoidance 1311 10 3.12 0.63 .78

Dimensions of social attitudesc

(5-points Likert Scale)11. Toughness 2022 20 2.58 0.46 .8012. Maliciousness 2022 20 2.55 0.46 .78

Dimensions of social attitudesd

(5-points Likert Scale)13. Alphaism 2022 6 3.09 0.51 .7214. Betaism 2022 8 2.78 0.47 .6515. Gammaism 2022 8 3.06 0.50 .6016. Deltaism 2022 6 3.27 0.49 .6017. Government intervention 1734 6 3.21 0.45 .4418. Harshness to outsiders 1734 6 3.13 0.44 .53

Valuese

(9-points Likert Scale)19. Power 2004 5 3.61 1.42 .7820. Achievement 2004 6 4.98 1.28 .8421. Hedonism 2004 3 4.60 1.45 .7022. Stimulation 2004 3 4.21 1.51 .7223. Self-direction 2004 6 5.14 1.27 .8324. Universalism 2004 8 4.89 1.28 .8525. Benevolence 2004 7 5.16 1.27 .8626. Tradition 2004 5 3.87 1.43 .6927. Conformity 2004 4 4.60 1.45 .7628. Security 2004 7 4.80 1.21 .7829. Spirituality 2004 3 5.08 1.48 .65

Dimensions of social normsf

(7-points Likert Scale)30. Uncertainty avoidance 2027 4 4.50 0.91 .4831. Future orientation 2027 5 4.26 1.03 .5532. Power distance 2027 5 4.98 1.05 .6533. Institutional collectivism 2027 4 4.38 0.91 .3434. Humane orientation 2027 5 4.49 1.09 .7835. Performance orientation 2027 3 4.49 1.01 .5036. In-group collectivism 2027 4 5.08 1.10 .5837. Gender egalitarianism 2027 5 3.51 0.92 .5138. Assertiveness 2027 4 4.27 0.97 .56

a IPIP (n.d.).b Neuroticism is scored in the opposite direction, indicating emotional stability.c Stankov & Knezevic, 2005.d Saucier, 2000.e Schwartz & Bardi, 2001.f House et al., 2004.


1.3. Summary of aims

In summary, the first aim of this study is to sample constructs froma range of domains that have been used in psychological studies ofcross-cultural differences. No single cross-cultural study to date hasincluded all four domains of personality, social attitudes, values, andsocial norms. The second aim is to break down total variability of thescales within each domain into an individual differences componentand the part that can be attributed to culture (country and societalclusters). The third aim is to examine the pattern of differencesbetween world regions on every variable to find out which regionsdeviate significantly from the rest.

2. Method

2.1. Participants

Applicants for undergraduate and graduate admission at U.S.universities who had taken TOEFL were invited to take part in thedimensions of culture study, for which they would be paid $20 or $50.Table 2 provides a breakdown of the participants into societal clusters(see House et al., 2004). Although the majority of participants whoindicated foreign nationality took this survey in their own country,some (less than 10%) of these participants provided their responsesfrom the U.S. sites.

A subsample of participants (N=429) in this study was recruitedfrom four U.S. colleges: Mercer County (NJ) Community College,Morgan State University (Baltimore, MD), Rice University (Houston,TX), and the University of Arizona. They were paid $50 to participatein an extensive survey that contained a battery of measures ofemotional intelligence, interests, attributions, and metacognitiveprocesses. Measures of culture were approximately one third of thewhole battery.

A total of 2029 people from 72 different countries participated inthis survey. Participants were asked to indicate their nationality, and


the answer to this question was coded as country. Korea and SouthKorea were kept as separate countries.3

A subsample of the total sample took measures of additionalpersonality traits (Variables 6 to 10 in Table 3; N=1,311) and twomeasures of social attitudes (Variables 17 and 18 in Table 3;N=1,734). After data cleaning, differing numbers of participantsremained for various scales. Summary statistics presented in Table 3are based on sample sizes listed in the first column. Since somecountries had small samples, it was decided to eliminate from theHLM analyses all countries that had fewer than 5 participants. Thenumber of countries was reduced to 45, and they are listed in Table 2.



Table 4Breakdown of total variance into percentage components related to individual, country, and societal clusters.

N Total variance % of total varianceindividuals

% of total variancecountry

% of total variancesocietal clusters

ANOVA F-test forsocietal cluster means

Big 5 personality traitsa

Extraversion 1962 .43 94.64 1.91 3.45 9.97Agreeableness 1962 .27 95.77 1.21 3.02 7.72Conscientiousness 1962 .33 90.02 3.72 6.26 17.54Neuroticism 1962 .44 95.29 2.03 2.66 6.40Openness 1962 .31 87.23 2.64 10.13 32.37

Average % of total variance: 92.59 2.30 5.15Additional personality traitsa

Belligerence 1264 .28 93.26 1.06 ns 5.68 9.35Conservatism 1264 .29 75.64 5.45 18.91 37.32Distrust 1264 .24 95.53 2.99 1.48 4.70Achievement-seeking 1264 .31 88.14 3.32 8.54 16.19Risk avoidance 1264 .39 96.02 3.98 .01 ns 2.99

Average % of total variance 89.71 3.36 6.92Dimensions of social attitudesb

Toughness 1963 .21 90.32 2.95 6.73 19.69Maliciousness 1963 .21 89.16 3.45 7.39 23.79

Average % of total variance: 89.74 3.20 7.06Dimensions of social attitudesc

Alphaism 1963 .28 83.97 5.59 10.44 22.35Betaism 1963 .23 87.07 5.95 6.98 17.95Gammaism 1963 .25 86.79 4.81 8.40 28.74Deltaism 1963 .25 87.00 6.14 6.86 16.02Government interventionism 1687 .20 93.98 1.58 4.44 10.05Harshness towards outsiders 1687 .20 92.25 1.92 5.84 14.48

Average % of total variance: 88.51 4.33 7.16Valuesd

Power 1932 1.96 93.77 2.10 4.12 12.04Achievement 1932 1.52 92.36 4.74 2.90 16.73Hedonsim 1932 2.01 96.43 3.56 0.01 ns 4.53Stimulation 1932 2.16 96.09 3.90 0.01 ns 9.47Self-direction 1932 1.51 91.03 5.40 3.57 15.82Universalism 1932 1.56 94.19 3.27 2.54 7.96Benevolence 1932 1.50 92.66 4.33 3.00 15.51Tradition 1932 1.99 88.81 2.01 ns 9.17 25.90Conformism 1932 2.02 88.36 4.09 7.55 21.66Security 1932 1.35 95.05 3.18 1.77 6.68Spirituality 1932 2.12 88.99 7.27 3.74 15.79

Average % of total variance: 92.52 3.99 3.49Dimensions of social normse

Uncertainty avoidance 1968 .86 83.73 6.69 9.58 26.84Future orientation 1968 1.08 82.27 7.59 10.14 33.04Power distance 1968 1.08 88.40 3.93 7.67 29.75Institutional collectivism 1968 .83 88.33 4.39 7.28 23.93Humane orientation 1968 1.23 81.96 5.70 12.33 32.20Performance orientation 1968 1.04 88.25 5.37 6.38 20.56In-group collectivism 1968 1.22 68.03 7.04 24.92 90.83Gender egalitarianism 1968 .88 83.74 6.04 10.22 25.48Assertiveness 1968 .90 91.94 6.99 1.07 ns 17.76

Average % of total variance: 84.07 5.97 9.95Conservatism composite 1926 16.02 74.93 5.93 19.13 51.45

Note. Bold indicates that individual variability greater than 95%. Italics indicates % of variance greater than 5%. For the F-tests, the degrees of freedom are df=8, N-9. ns = notsignificant.

a IPIP (n.d.).b Stankov & Knezevic, 2005.c Saucier, 2000.d Schwartz & Bardi, 2001.e House et al., 2004.

4 The program used for test delivery was WebSurveyor.


The first column of Table 4 lists the total number of participantsincluded in the HLM analysis for each measure.

The average age of participants was 22.60 (SD=5.54). The sampleconsisted of 52.4% females. At the time of testing, 15.7% of participantshad completed less than 12 years of formal education, 19.7% hadcompleted 13 to 14 years, 43.8% had completed 15 to 18 years, and18.5% reported having 18 and more years of formal education.

The samples used in this study are far from being representative ofthe populations from which they arise. Some of the issues that limitthe interpretation of the results will be addressed in the discussionsection at the end of this paper.


2.2. Measures

A total of 276 items that formed 38 scales embedded in fourdifferent instruments were employed in this study. They were alldelivered over the Internet in English. At the beginning of the testingsession, participants were given a brief description of the task aheadand promised a $20 (or $50) payment for the completion of thequestionnaires. If they agreed, they were asked to log on onto aspecified Web site.4 Time for completing the questionnaires varied



5 Schwartz now uses 10 scales after dropping spirituality.


from around 45 to 120 min. Brief scale descriptions and exampleitems are as follows.

2.3. Domain: personality traits

There has been an accumulation of data on cross-culturaldifferences in basic personality traits from more than 60 countries(McCrae & Allik, 2002; see also Saucier & Goldberg, 2002, 2003;Schmitt et al., 2007; Terracciano et al., 2005). For the measurement ofThe Big Five personality factors, a 50-item scale available from theInternational Personality Item Pool (2008) was used.

1. Extraversion.2. Agreeableness.3. Conscientiousness.4. Neuroticism (or emotional stability).5. Openness.

In addition to the traditional Big Five factors, the present battery ofinstruments includes measures of five factors that cover areas ofpersonality identified in the work of Tellegen (see Patrick, Curtin, &Tellegen, 2002), downloaded from the IPIP Web site. The scales wereselected for this work to overdetermine the measurement ofsomewhat nasty and antisocial aspects of personality that bridge thegap between traditional positive self-evaluative Big Five traits and(Anti-) Social Attitudes measures. For each scale, five items werereverse-scored.

6. Belligerence. Example: “I do things out of revenge.”7. Conservatism. Example: “I believe laws should be strictly enforced.”8. Distrust. Example: “I dislike people.”9. Achievement-seeking. Example: “I do more than what's expected of

me.”10. Risk avoidance. Example: “I would never go hang gliding or

bungee jumping.”

2.4. Domain: social attitudes

Toughness and maliciousness. The social judgments scale consistingof two components was based on work designed to examinedemographic and psychological aspects of antisocial and criminalbehavior in Serbia during the early 1990s. Stankov and Knezevic's(2005) study compared performance of Serb and Australian studentson these scales, and measures used in the present study are derivedfrom that earlier work. A total of 40 items are rated on a 5-pointLikert-type scale ranging from 1 (strongly disagree) to 5 (stronglyagree). These items were classified into two instruments composed of20 items each.

11. Toughness. Examples: “I am tired of being forced to do things,” and“I hate (despise) anyone in authority, whether my father, myteacher, or my boss.” Five items were reverse-scored.

12. Maliciousness. Examples: “Some people should not expectcompassion from me,” and “I resent seeing people sufferingbecause it affects my ability to enjoy myself.” Five items werereverse-scored.

Saucier's -isms. Saucier's (2005) 28-item questionnaire measuringfour dimensions was employed:

13. Alphaism. Example: “Religion should play the most important rolein civil affairs.” Three out of six items were reverse-scored.

14. Betaism. Example: “Worldly possessions are the greatest good inlife.” Four out of eight items were reverse-scored.

15. Gammaism. Example: “I love and am devoted tomy country.” Fourout of eight items were reverse-scored.

16. Deltaism. Example: “Some objects have magical powers.” Threeout of six items were reverse-scored.


Two additional scales from Saucier's work on -isms were alsoincluded:

17. Government interventionism. Example: “Wealthy people shouldhave a higher tax rate than poor people.” Three out of six itemswere reverse-scored.

18. Harshness towards outsiders. Example: “I approve the imposing ofrestrictions on immigration.” Three out of six items were reverse-scored.

In comparison to the main four -isms dimensions that emergedfrom Saucier's work, these two additional scales (governmentinterventionism and harshness towards outsiders) are less well-established. They have been employed with U.S. samples only andtend to reflect mostly political beliefs held by those belonging to thetwo main parties in the United States—Republicans and Democrats.

2.5. Domain: values

Schwartz's Values Survey. Schwartz and colleagues (see Schwartz &Bardi, 2001) developed a theory of human values, postulating 11 basicdomains along which individuals and societies may be differentiated.According to them, values originate from universal requirements ofhuman conditions, such as biological, social, and survival needs. TheValue Survey is used to assess how important each value is as aguiding principle in one's own life. The 57 items are rated on a 9-pointLikert-type scale, ranging from—1 (opposed to my values) to 7 (ofsupreme importance), and those items were classified into 11 scales(domains), each having three to eight items.5 The 11 values scales areas follows:

19. Power. Assessing the importance of authority, wealth, socialpower, public image, and social recognition.

20. Achievement. Assessing the importance of ambition, success,capacity, influence, and intelligence.

21. Hedonism. Assessing the importance of pleasure and enjoyment oflife.

22. Stimulation. Assessing the importance of variety and excitement.23. Self-direction. Assessing the importance of creativity, freedom,

independence, and curiosity.24. Universalism. Assessing the importance of broadmindedness,

social justice, equality, and the world at peace.25. Benevolence. Assessing the importance of helpfulness, loyalty,

forgiveness, honesty, and responsibility.26. Traditionalism. Assessing the importance of respect of tradition,

humility, devoutness, and moderation.27. Conformity. Assessing the importance of obedience, self-disci-

pline, and politeness.28. Security. Assessing the importance of social order, family security,

national security, and sense of belonging.29. Spirituality. Assessing the importance of meaning of life, sense of

inner harmony, and sense of detachment.

2.6. Domain: social norms

GLOBE. There are nine main social norm dimensions that emergedfrom the GLOBE research project (see House et al., 2004). In theInternet version of the questionnaire that was used in this study, thereis an introductory incomplete sentence “IN MY SOCIETY…” at the topof each page, and the participant has to answer on a 7-point Likert-type scale ranging from 1 (strongly agree) to 7 (strongly disagree). Atotal of 39 statements are used to assess the GLOBE dimensions:

30. Uncertainty avoidance. Example: “Most people lead highlystructured lives with few unexpected events.”



6 Both intraclass correlation and ANOVA F-test are calculated as ratios that haveestimates of the between variances in the numerator. Denominators, however, differ.For intraclass correlation, the denominator is total variance (i.e., the sum of betweenand within variances). For F-test, the denominator is the estimate of the (pooled oversocietal clusters) within variance.


31. Future orientation. Example: “Most people live for the presentrather than the future.”

32. Power distance. Example: “Followers are expected to obey theirleaders without question.”

33. Institutional collectivism. Example: “Leaders encourage grouployalty even if individual goals suffer.”

34. Humane orientation. Example: “People are generally very tolerantof mistakes.”

35. Performance orientation. Example: “Students are encouraged tostrive for continuously improved performance.”

36. In-group collectivism. Example: “Employees feel great loyaltytoward their organization.”

37. Gender egalitarianism. Example: “Boys are encouraged more thangirls to attain higher education.”

38. Assertiveness. Example: “People are generally dominant in theirrelationships with each other.”

2.7. Missing data

There are missing data in this study due to two design issues. First,six scales were added to the battery after the collection of data hadbegun and approximately 300 people were tested. The six scales wereadditional personality traits (Scales 6 to 10) and two of Saucier'smeasures (scales 17 and 18). The total samples that were available forthe analyses of these measures can be seen in the first column inTable 3. Second, the U.S. sample was given questionnaires as part ofanother study and, because of time constraints, participants were notgiven additional personality traits (Scales 6 to 10). For the HLManalyses, the sample was further reduced because of the exclusion ofthose countries that had fewer than five participants (see Table 4 forthe sample sizes employed in HLM analyses).

3. Results

3.1. Descriptive statistics

Table 3 presents descriptive statistics and Cronbach's alphas. Theoverall means and standard deviations for the variables included inthis study are expressed as the averages over all items defining a scale.This makes it possible to compare the average endorsements ofdifferent statements that employ the same Likert scale format andpresent them in the figures in a latter section of this paper. Overall,descriptive statistics for the variables used in this study are within theexpectation.

Given the number of items within the scales, it is perhapssurprising that Cronbach's alphas for thirty scales are above .60 andthirty five out of thirty eight scales are above .50. Only one scale(Institutional Collectivism) has truly dubious internal consistencyreliability of .34. This scale and perhaps two others whose Cronbach'salphas are in the .40 to .50 range could have been excluded from theanalyses. They are retained because previous work with these scaleshas shown satisfactory reliability. Also, HLM analyses reported beloware for single variables and the reader can easily ignore those variableswith low reliability; themain findings of this paper are not affected bythe exclusion of a few variables.

Since the number of participants from some countries was small,Cronbach's alphas are not reported for individual countries. Aspointed out by a reviewer of this paper, the size of reliabilitycoefficients will certainly vary from country to country (seecontributions to Grigorenko, 2009, volume). Perhaps it is encouraging,however, that Stankov and Lee (2009) report considerable similaritiesof factorial structure across different societal clusters on variablesused in the present paper. In theory at least, correlations among thevariables that are captured by factor loadings provide lower boundson reliabilities since common variance by definition does not containerror. Thus, we can assume on the basis of Stankov and Lee's (2009)


findings that reliabilities within societal clusters are likely to besatisfactory.

3.2. Hierarchical linear modeling: the effects of culture

This section focuses on the amount of total variance of a variablethatmay be attributed to culture (both countries and societal clusters)as opposed to the variance that resides within the individuals.

Table 4 provides summary results for the HLM analyses of the 38scales employed in this study. The second column in this tablepresents the total amount of variance for a given variable. The valuesin this column correspond to the square of standard deviations inTable 3. The discrepancies are due to different numbers of participantsin the total sample and in the sample for the HLM analysis.

The next three columns provide the percentages of the totalvariance that can be attributed to individuals, countries, and societalclusters. Technically, the countries and societal cluster componentsare known as the intraclass correlations (i.e., the proportion of thetotal variance that can be attributed to the between-variancecomponent6). Output for the HLM analyses provides chi-squaresignificance tests for Level 2 and Level 3 (i.e., countries and societalclusters) components. The majority of values for the total variance forcountry and for societal clusters are significant at the .05 level; thosethat are not significant are labeled “ns” in Table 4.

The last column shows ANOVA (one-way) F-tests for testing thedifferences between the societal clusters. All F-tests are statisticallysignificant, therefore, if onewere to assume that the participants wererandomly distributed between the groups, one can conclude thattherewere differences (pb .05) between them. Notice, however, that asignificant F-test may correspond to a miniscule amount of variance.For example, for hedonism, although the F-test is significant (4.53),the amount of variance accounted for by the societal clusters is only.01%, which is insignificant from any point of view. Thus, the F-test istoo sensitive in the present study. In general, however, the F-tests and% of total variance societal clusters columns tell the same story. Thediscrepancies arise because of the differences mentioned in Footnote6 and because F-tests operate on societal clusters only and thereforehave some of the countries' variability included. Level 3 of the HLManalysis is restricted to societal clusters.

The 5% rule. To evaluate the outcome of the HLM analyses, thisstudy uses the value of 5% as a cut-off. This is an arbitrary choice,based in part on guidelines proposed by Cohen (1988) that declareincremental validity lower than 2% as negligible. Although a casecould be made for using 2% for country and 2% for society, this studyused 5% (i.e., assuming 2.5% instead of 2% for each component) incombination. Thus, if a variable has 95% of the variance contributing toindividual differences and only 5% of the variance contributing toculture, the effect of culture can be deemed to be of little practicalimportance.

The 5% cut-off value is often employed in predictive validitystudies to assess the incremental validity of a variable over othervariables that are already included in the regression equation. Thisstudy used the same arbitrary rule to assess practical importance ofthe contributions of countries and societal clusters. Thus, if a variablehas more than 5% of variance attributed to countries or 5% to societalclusters, the effect will be treated as practically significant for thisparticular source of variability.

Individual vs. culture (countries and societal clusters). A commonfinding in the application of the HLM procedures in psychology andeducation is the strong role of individual variability. This is evident in



7 Essentially, the same pattern of results was obtained when a compositeconservatism score was calculated from 12 variables—the 7 listed in the main textplus (with appropriate imputation) conservatism, harshness towards outsiders,government interventionism, humane orientation, and individual collectivism. Theselast 5 were excluded from the calculation of conservatism composite reported in themain body of the paper because of the large amount of missing data.


Table 4. The percentage of total variance accounted for by theindividual level ranges from 68.03% (in-group collectivism) to 96.43%(hedonism). This is in agreement with the findings reported in theliterature (see Poortinga & van Hemert, 2001; van Hemert, van deVijver, Poortinga, & Georgas, 2002). For the majority of variables, thevariance accounted for by culture is between 5% and 20%. Thestrongest effects of culture are present in the in-group collectivism(31.97%) and conservatism (24.36%) subscales.

Using the 5% rule, seven variables show negligible culturaldifferences (i.e., 100% minus the value in column labeled “% of totalvariance individual” in Table 3). These are agreeableness (4.23%),neuroticism (4.71%), distrust (4.47%), risk avoidance (3.98%), hedo-nism (3.57%), stimulation (3.91%), and security (4.95%). Out of 38variables, 31 show the effects of culture. Only 1 variable from the BigFive domain (openness, 12.77%) and 3 variables out of 11 from thedomain of values (tradition [11.19%], conformity [11.64%], andspirituality [11.01%]) have percentages of cultural level variancesthat are higher than 10%. Overall, as can be seen from the averagepercentages of the total variance for these two domains, both values(7.48%) and Big Five personality (7.41%) seem to be less affected bycultural influences than either social attitudes (11.49% for Saucier'smeasures and 10.26% for Stankov/Knezevic measures) or social norms(15.93%). Notice that 1 of the 5 additional personality variables fromthe International Personality Item Pool (IPIP, conservatism [24.36%])is more sensitive to cultural effects than all other personalitymeasures. Mostly because of that particular variable, the averagepercentage of variance accounted for by the additional IPIP person-ality measures is close to the percentages accounted for by the socialattitudes scales. Notice also that additional Saucier's variables(harshness towards outsiders and government interventionism)show smaller cultural differences relative to the other dimensionscaptured by Saucier's measure. Thus, if these two variables were to beremoved from the average percentage of total variance for thedimensions of social attitudes (Saucier) in Table 4, the average relatedto culture would be increased from 11.49% (i.e., 4.33% plus 7.16%) to13.79%.

There are few studies that report intraclass correlations for thevariables used in this paper. Poortinga and van Hemert (2001)reported the proportions of cultural variance for the EysenckPersonality Questionnaire and for Schwartz's value scale that werehigher than in the present study. In their study, extraversion andneuroticism from 38 countries captured 17% and 16% of total variance,respectively (5.23% and 5.20% in this study). For Schwartz's valuescale, Poortinga and van Hemert reported intraclass correlations thatranged from 6% (for stimulation) to 21% (for conformity). In thisstudy, stimulation and conformity are also at the two extremes interms of size of cross-cultural differences, but the amount of varianceattributed to culture is smaller (3.91% for stimulation and 11.64% forconformity). This study's results are also comparable to the recentfindings with mathematics achievement scores for PISA 2003, whichreported the amount of between-countries variance in that study as10% (Organisation for Economic Co-Operation and Development,2004, p. 439).

It is apparent from the previously mentioned account that the dataare in agreement with the hypothesis that social norms scales are themost influenced by culture, followed by, as expected, social attitudes,and personality. A surprising finding in the data is the poor sensitivityto cultural influences of most measures of values. One explanation isthe fact that all of the participants in this study have a relatively highlevel of education, with over 60% having more than 15 years of formaleducation. It is possible that educational systems across the globehave been exerting effects on values that lead to the minimization ofcross-cultural differences in this domain. Another explanation is thepossibility that cultural universals are more common among themeasures of values than among the other measures employed in ourstudy.


Countries vs. societal clusters. The data in this study allow for theexamination of the relative roles of two types of cultural influences—those captured by the country effects (perhaps reflecting politicalinfluences to some extent) and those captured by the effects ofsocietal clusters (world region cultural influences). It is clear in thepresent data that differences between societal clusters are morepronounced than differences between countries. An exception to thisobservation is the domain of values. This is evidenced by the fact that,for personality, social attitudes, and social norms, the percentage oftotal variance accounted for by the societal clusters is greater than thepercentage accounted for by the countries, both at the variable leveland as the average for the domain. The overall conclusion is that, inthe present data, cultural effects arise mostly from the differencesbetween societal clusters. The attempted two-level analyses withindividual and country levels (no societal clusters) are in generalagreementwith this conclusion; the percentage of variance accountedfor by the countries is smaller than the percentage accounted for bythe societal clusters.

Cross-cultural differences in conservatism. Stankov (2007) reportedthe outcome of factor analysis of essentially the same set of variablesbased on a sample (N=1255) of U.S. community college students.Conservatism was one factor that cut across the four domains (seealso Stankov & Lee, 2008, 2009). It is instructive to have a closer lookat cross-cultural differences on a composite representing this factor inthe present data because a number of variables that defined this factorin Stankov's (2007) study also show a strong cultural component inthe present study. A composite conservatism score was formed byadding unstandardized scores from the following seven scales:conscientiousness, alphaism, gammaism, deltaism, tradition, confor-mity, and in-group collectivism.7

The last row in Table 4 presents the breakdown of the totalvariance for this conservatism composite. Clearly, in comparison toindividual variables, cross-cultural differences on the conservatismcomposite are considerable, with 25.07% of the total varianceaccounted for by the effects of countries and societal clusters. Themain part of the variance, again, is related to societal clusters(19.13%).

Societal clusters: Patterns of cross-cultural differences. Figs. 1through 4 present the mean levels of endorsement for the ninesocietal clusters on scales employed in the present study. To savespace and because of the smaller effects of Level 2 (countries) inTable 3, analogous country-level information is not presented. Also, tosave space, only the two scales from the domains of personality(conscientiousness and openness) and values (tradition and confor-mity) that have more than 5% of the total variance accounted for bythe societal clusters are reported. Fig. 1 presents the curvesconnecting societal clusters' means for pairs of scales from threedomains: personality, values, and social attitudes. While examiningthe pattern of mean differences in Fig. 1, keep in mind that toughness,maliciousness, conscientiousness, and openness are measured on a 5-point Likert scale, while tradition and conformity are measured on a9-point Likert scale (−1 to 7 was converted to 1 to 9). Clearly, thepattern of means for toughness and maliciousness and, to someextent, for conscientiousness and openness are similar across thesocietal clusters. Although the F-tests in Table 4 for these fourvariables are significant, the curves are relatively flat. The same cannotbe said about the values of tradition and conformity. Two observationscan be made. First, European clusters are lower than the other regionsof the world on these two variables. Second, Sub-Saharan Africans



0

1

2

3

4

5

6

Lik

ert

Sca

le

CONSCIEN

OPENNESS

Toughness

Maliciousness

Tradition

Conformism

Fig. 1. Societal clusters means on personality (conscientiousness [CONCIEN] and openness), social attitudes (toughness and maliciousness), and values (tradition and conformism).For personality and social attitudes, Likert scale ranges from 1 to 5. For values, Likert scale ranges from 1 to 9.

2

2.5

3

3.5

4

Lik

ert

Sca

le

ALPHA

BETA

GAMMA

DELTA

GOVERNM

HARSHNES

Fig. 2. Societal clusters means on social attitudes (Saucier's -ism measures). Likert scale ranges from 1 to 5.


score higher on these two variables than most other regions of theworld.

Fig. 2 presents the curves connectingmeans for societal clusters forsocial attitude measures based on Saucier's (2000) work. Again, themost remarkable is the finding of relatively high standing of Sub-Saharan Africans on all but two measures (gammaism [Westerndemocracy beliefs] and harshness towards outsiders). Figs. 3 and 4present curves for social norms based on variables from the GLOBEstudy (House et al., 2004). In Fig. 3, relative to other clusters, EastEurope and Latin America score high on power distance and low onuncertainty avoidance, future orientation, institutional collectivism,and humane orientation. In Fig. 4, Sub-Saharan Africans score low ongender egalitarianism and Anglos and two European clusters (Latinand Germanic) score low on in-group collectivism.

Fig. 5 presents the means for societal clusters on the conservatismcomposite and an interesting pattern of endorsement is clearlydiscernible. TwoEuropeanregions (Germanic and LatinEurope)expressless conservative views than Sub-Saharan Africa, Southern Asia, LatinAmerica, and the Middle East. On the seven-variable composite ofconservatism reported here, East Europeans, Anglos, and ConfucianAsians are in the middle.8 For this composite, the mean over all societalclusters is 26.49 and standard deviation is 3.90. The difference between

8 When conservatism is defined in terms of subscales mentioned in Footnote 7, theoverall pattern of results changes slightly—East Europe is closer to the other twoEuropean clusters.


themost liberal (Germanic Europe, mean 23.11) andmost conservative(Sub-Saharan Africa, mean 29.36) is considerable: 1.60 standarddeviations. It is perhaps of some interest that the Anglo cluster (mostlythe U.S. sample) is not aligned with the European clusters in Fig. 5.

4. Summary and discussion

Psychological dimensions of culture that are the focus of thepresent study encompass constructs from fourmajor domains, each ofwhich has been studied extensively in the past. For the first time,some of the best available measures assessing the domains ofpersonality, social attitudes, values, and social norms were adminis-tered to a large sample of participants from around the globe. Theissue of interest is the relative contribution of culture to the varianceof 38 measures from these four domains.

The largest percentage of total variance (between 68.03% and96.43%) is related to individual differences and, on average, about 11%is related to culture. This is typical of work in psychology that collectsdata based on nested levels of analysis. If anything, this shows that thepsychology of individual differences is important and, perhaps, that anextreme version of the cultural relativism hypothesis is wrong. Does itdeny the role of culture? That depends on one's point of view. Fromthe social policy point of view, does 18% of variability of performancein mathematics reported by Raudenbush and Bryk (2002, p. 71) thatcan be attributed to schools (with the rest being attributed toindividuals), imply that high performing schools should not be



2

2.5

3

3.5

4

4.5

5

5.5

6

Lik

ert

Sca

le

UNCEAVO

FUTUORIE

POWEDIST

INSTCOLL

HUMAORIE

Fig. 3. Societal clusters means on social norms (uncertainty avoidance [UNCEAVO], future orientation [FUTUORIE], power distance [POWEDIST], institutional collectivism [INSTCOLL],and humane orientation [HUMAORIE]). Likert scale ranges from 1 to 5.


rewarded for their achievements? Or does heritability of intelligenceof .80 as reported in some studies imply that there is no role foreducation? Clearly, the answers are no to both questions; hugeamounts of investment into education by all societies around theglobe speak to the contrary. As became clear in from the work ofHedges, Laine, and Greenwald (1994), it is not the investment but thepayoff on investment that matters in this kind of argument.Analogously, does 11% of the variability that is related to culturemean that one should start neglecting cultural effects? Given thetrend towards globalization and the potential for friction that mayarise from cultural misunderstanding, the answer again has to be “no”because of the payoff issues. In other words small effect sizes need tobe put in a socially responsive perspective.

From the scientific point of view, the findings of the present studyindicate that the size of cross-cultural differences depends on thenature of the psychological process under investigation. The effectsvary depending on whether one focuses on measures of personality,social attitudes, values or social norms. The smallest and perhapsscientifically negligible effects of culture are on personality (private,biologically determined psychological traits) and the largest are onmeasures of social norms (perception of rules prevalent in thesociety), with social attitudes being in the middle. An unexpectedfinding was a small, comparable to personality, effect of culture on

0

1

2

3

4

5

6

7

Lik

ert

Sca

le

Fig. 4. Societal clusters means on social norms (performance orientation [PERFORIE], in-g[ASSERTIV]). Likert scale ranges from 1 to 5.


measures of values. A possible explanation for this outcome is theequalizing role of education on values and a selection of participantsfor this study from a highly educated population of TOEFL test takers.Another possibility is that values are indeed universal psychologicalconstructs, relatively impervious to cultural influences.

Comparisons of the mean levels for societal clusters (worldregions) shows that three European clusters (Germanic, Latin, andEastern) tend to endorse conservative statements from all fourpsychological domains less strongly than the rest of the world. Inour studies, the conservatism/liberalism dimension has emerged asone of the main dimensions of cross-cultural differences (Stankov,2007, 2009). Since one of the main cross-cultural dimensions in theliterature today is individualism/collectivism (Smith et al., 2006;Triandis, 1995), it will be important to further examine therelationship between this dimension and conservatism in futurestudies. Although the GLOBE in-group collectivism measure is a partof the conservatism composite in the present study, this relationshipdoes not imply the identity of the two constructs.

Sub-Saharan Africans score low on gender egalitarianism and highon measures of social attitudes (religious sources of authority[alphaism], unmitigated self interest [betaism], and personal spiritu-ality [deltaism]) than people from other parts of the world. They alsoscore high on tradition and conformity. East Europeans and Latin

PERFORIE

INGRCOLL

GENDEGAL

ASSERTIV

roup collectivism [INGRCOLL], gender egalitarianism [GENDEGAL], and assertiveness



CLUSTER

AngloConfucianAsia

SouthernAsia

Middle EastSub-Saharan

Africa

LatinAmerica

EasternEurope

GermanicEurope

LatinEurope

Co

nse

rvat

ism

30

28

26

24

22

Fig. 5. Societal clusters means on conservatism composite. Likert scale ranges from ? to ?.


Americans score low on several measures of social norms suggesting,perhaps, that people from these two world regions have a somewhatcynical attitude towards political institutions in their societies.

Culture consists of two parts in this study—countries and societalclusters. Both are important, but the role of societal clusters is morepronounced on the majority of the measures, with the exception ofmeasures of values.

While contemplating these results, one must keep in mind thedesign issues that place limitations on the generalizability of thefindings. There are four issues that need to be addressed here. First,the language employed in this survey was English and there areindividual differences in language proficiency among the participants.This paper did not control for such effects. However, Stankov and Lee(2008) reported correlations between the present measures andTOEFL and Synonyms Vocabulary test performances based on asmaller (N=288) sample of participants. Also, Stankov (2007)reported similar findings with native (U.S.) speakers of English whoprovided their SAT® score. The results suggest that languageproficiency is not crucial for understanding the dimensions of cultureas studied in this approach. Second, a study by Harzing (2005)investigated whether the language of the questionnaire influencesresponse patterns. In particular, she tested whether responding in acommon language (English) leads to a homogenization of responsesacross countries, hence obscuring national differences. Half of thestudents in each country received an English-language questionnaire,while the other half received the same questionnaire in their nativelanguage. Harzing reported that differences across countries weresignificantly smaller when the English-language questionnaire wasused. Thus, somewhat low effects of culture obtained in the presentstudy may be at least in part attributed to the common language andthe use of native language may produce larger effects of culture.

Third, the results of hierarchical linear modeling procedures needto be interpreted with caution because of the small sample size atLevel 3 (societal clusters). Raudenbush and Bryk (2002) emphasized


that inferences about the variance components “depend on the large-scale properties of maximum likelihood estimates” (p. 283). Thismeans that the accuracy of the variance components estimatesdepend on the sample size at a given level. Thus, the total sample sizeat the individual level (N=1968) is large and the sample size(N=45) at the country level is moderate. On the other hand, sincethere are only nine societal clusters, the estimates at Level 3 may notbe stable and the findings at that level need to be interpreted with adegree of caution.

Finally, participants in the present study are all literate and, in fact,well-educated. It is hard to speculate about the extent to which theseresults will be replicated within less educated samples. They are alsobilingual and perhaps bicultural. This raises concerns about the extentto which they can be valid and reliable representatives of the culturethey say they are from.

Acknowledgments

I am grateful to J. Steinberg, Y. Jia, and A. Oranje for their help withHLM analyses reported in this paper and to Nat Kogan and LarryStricker for comments on an earlier version of this paper.

References

Church, A. T. (2000). Culture and personality: Toward an integrated cultural traitpsychology. Journal of Personality, 68, 651−703.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2nd ed. Mahwah,NJ: Lawrence Erlbaum Associates.

Grigorenko, E. L. (Ed.). (2009). Multicultural psychoeducational assessment. New York:Springer Publishing Company.

Harzing, A. -W. (2005). Does the use of English-language questionnaires in cross-national research obscure national differences? International Journal of CrossCultural Management, 5(2), 213−224.

Hedges, L. V., Laine, R. D., & Greenwald, R. (1994). Does money matter? A meta analysisof studies of the effects of differential school inputs on student outcomes.Educational Researcher, 23(3), 5−14.




Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions andorganizations across nation, 2nd ed. London: Sage.

House, R. J., Hanges, P. J., Javidan, M., Dorfman, P. W., & Gupta, V. (2004). Culture,leadership, and organizations: The GLOBE study of 62 societies. Thousand Oaks, CA:SAGE Publications.

Inglehart, R., & Carballo, M. (1997). Does Latin America exist? (And is there a Confucianculture?): A global analysis of cross-cultural differences. Political Sciences andPolitics, 30(1), 34−46.

Inglehart, R., Basañez, M., & Moreno, A. (1998). Human values and beliefs: A cross-cultural sourcebook. Ann Arbor, MI: The University of Michigan Press.

International Personality Item Pool: A scientific collaboratory for the development ofadvanced measures of personality traits and other individual differences. (n.d.).Retrieved March 14, 2008, from http://ipip.ori.org/.

International Social Survey Program (1997). International social science program: Workorientations II, 1997 (ICPSR version) [data file]. Ann Arbor, MI: Inter-universityConsortium for Political and Social Research.

Leung, K., & Bond, M. H. (2004). Social axioms: A model for social beliefs inmulticultural perspective. Advances in Experimental Social Psychology, 36, 119−197.

Leung, K., Bond, M. H., Carrasquel, S. R., Muñoz, C., Hernádez, M., Murakami, F., et al.(2002). Social axioms: The search for universal dimensions of general beliefs abouthow the world functions. Journal of Cross-Cultural Psychology, 33, 286−302.

Lustig, M. W., & Koester, J. (2003). Intercultural competence: Interpersonal communica-tion across cultures, 4th ed. New York: Allyn & Bacon/Longman.

McCrae, R. R. (2002). NEO-PI-R data from 36 cultures. In R. R. McCrae, & J. Allik (Eds.),The five-factor model of personality across cultures. New York: Kluwer Academic.

McCrae, R. R., & Allik, J. (2002). The five-factor model of personality across cultures. NewYork: Kluwer Academic.

McCrae, R. R., & Terracciano, A.79 members of the Personality Profiles of CulturesProject. (2005). Personality profiles of cultures: Aggregate personality traits.Journal of Personality and Social Psychology, 89, 407−425.

Organisation for Economic Co-Operation and Development (2004). Learning fortomorrow's world: First results from PISA 2003. Paris, France: Author.

Patrick, C. J., Curtin, J. J., & Tellegen, A. (2002). Development and validation of a briefform of the Multidimensional Personality Questionnaire. Psychological Assessment,14, 150−163.

Poortinga, Y. H., & van Hemert, D. A. (2001). Personality and culture: Demarcatingbetween the common and the unique. Journal of Personality, 69(6), 1033−1060.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications anddata analysis methods, 2nd ed. Newberry Park, CA: Sage.

Roccas, S., Sagiv, L., Schwartz, S. H., & Knafo, A. (2002). The Big Five personality factorsand personal values. Personality and Social PsychologyBulletin., 28, 789−801.

Rokeach, M. (1973). The nature of human values. New York: The Free Press.


Saucier, G. (2000). Isms and the structure of social attitudes. Journal of Personality andSocial Psychology, 78, 366−385.

Saucier G. (2004). Personality and ideology: One thing or two? Unpublished manuscript.Saucier G. (2005). A brief measure of the four factors in the Survey of Dictionary-Based

Isms (SDI). Unpublished manuscript.Saucier, G., & Goldberg, L. R. (2002). Assessing the Big Five: Applications of 10

psychometric criteria to the development of marker scales. In B. de Raad, & M.Perugini (Eds.), Big Five assessment (pp. 29−58). Goettingen, Germany: Hofrege &Huber.

Saucier, G., & Goldberg, L. R. (2003). The structure of personality attributes. In M. B.Barrick, & A. M. Ryan (Eds.), Personality and work: Reconsidering the role ofpersonality in organizations. San Francisco: Jossey-Bass.

Schmitt, D. P., Allik, J., McCrae, R. R., & Benet-Martinez, V. (2007). The geographicdistribution of Big Five Personality traits: Patterns and profiles of human self-description across 56 nations. Journal of Cross-Cultural Psychology, 38, 173−212.

Schwartz, S. H. (2003). Basic human values: Their content and structure across cultures.In A. Tamayo, & J. Porto (Eds.), Valores e trabalho [Values and work]. Brasilia, Brazil:Editora Universidade de Brasili.

Schwartz, S. H., & Bardi, A. (2001). Value hierarchies across cultures: Taking asimilarities perspective. Journal of Cross Cultural Psychology, 32, 268−290.

Smith, B. P., Bond, M. H., & Kagitcibasi, C. (2006). Understanding social psychology acrosscultures: Living and working in a changing world. Thousand Oaks, CA: SAGE.

Stankov, L. (2007). The structure among measures of personality, social attitudes,values, and social norms. Journal of Individual Differences, 28, 240−251.

Stankov, L. (2009). Conservatism and cognitive ability. Intelligence, 37, 294−304.Stankov, L., & Knezevic, G. (2005). Amoral social attitudes and value orientations among

Serbs and Australians. Australian Journal of Psychology, 57, 115−129.Stankov, L., & Lee, J. (2008). Culture: Ways of thinking and believing. In G. J. Boyle, G.

Matthews, & D. Saklofske (Eds.), The handbook of personality theory and testing(pp. 560−575). : Sage Publications.

Stankov, L., & Lee, J. (2009). Dimensions of cultural differences: Pancultural, etic/emic,and ecological approaches. Learning and Individual Difference, 19(3), 339−354.

Sternberg, R. J., & Grigorenko, E. L. (2004). Culture and competence: Context of life success.Washington, DC: American Psychological Association.

Terracciano, A., Abdel-Khalek, A. M., Ádám, N., Adamovová, L., Ahn, C. -k., Ahn, H. -n.,et al. (2005). National character does not reflect mean personality trait levels in 49cultures. Science, 310, 96−100.

Triandis, H. C. (1995). Individualism and collectivism. Boulder, CO: Westview.van Hemert, D. A., van de Vijver, F. J. R., Poortinga, Y. H., & Georgas, J. (2002). Structural

and functional equivalence of the Eysenck Personality Questionnaire within andbetween countries. Personality and Individual Differences, 33, 1229−1249.



individual, country and societal cluster differences on measures of personality, attitudes, values,...

Documents