Researching multiple publics through latent profile analysis: Similarities and differences in science and technology attitudes in China,Japan,South Korea and the United States
Restricted accessResearch articleFirst published online February, 2019
Researching multiple publics through latent profile analysis: Similarities and differences in science and technology attitudes in China,Japan,South Korea and the United States
How science and technology attitudes vary across the United States, China, South Korea and Japan – all of which top Bloomberg’s list of high-tech centralization – is explored through data from the sixth wave of the World Values Survey (2010–2014). The following study examines the presence of different types of attitudinal groups using latent profile analysis. Not only do unique attitudinal groups exist in each country, but each group is uniquely influenced by select demographic characteristics, including education, age, gender, religiosity, employment status and individual interaction with technology. The findings provide insight into public attitudes towards science and technology across social and cultural contexts and generate nuanced understandings of similar and different attitudinal groups in East Asia and the United States.
AchterbergPde KosterWvan der WaalJ (2017) A science confidence gap: Education, trust in scientific methods, and trust in scientific institutions in the United States, 2014. Public Understanding of Science26(6): 704–720.
2.
AlemánJWoodsD (2016) Value orientations from the World Values Survey: How comparable are they cross-nationally?Comparative Political Studies49(8): 1039–1067.
3.
AllumNSturgisPTabouraziDBrunton-SmithI (2008) Science knowledge and attitudes across cultures: A meta-analysis. Public Understanding of Science17(1): 35–54.
4.
AsonguSA (2017) Knowledge economy gaps, policy syndromes, and catch-up strategies: Fresh South Korean lessons to Africa. Journal of the Knowledge Economy8(1): 211–253.
5.
AsparouhovTMuthénB (2014) Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal21(3): 329–341.
6.
BakHJ (2001) Education and public attitudes toward science: Implications for the ‘deficit model’ of education and support for science and technology. Social Science Quarterly82(4): 779–795.
7.
BallR (2010) Cultural values and public policy: The case of international development aid. Quarterly Review of Economics and Finance50(1): 3–16.
8.
BesleyJC (2018) Audiences for science communication in the United States. Environmental Communication. Epub ahead of print 3 May. DOI: 10.1080/17524032.2018.1457067.
CohenJ (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd edn.Hillsdale, NJ: Lawrence Erlbaum Associates.
11.
CollierZKLeiteWL (2017) A comparison of three-step approaches for auxiliary variables in latent class and latent profile analysis. Structural Equation Modeling: A Multidisciplinary Journal24(6): 819–830.
12.
CollinsLMLanzaST (2010) Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. New York, NY: John Wiley & Sons.
13.
CormickCRomanachLM (2014) Segmentation studies provide insights to better understanding attitudes towards science and technology. Trends in Biotechnology32(3): 114–116.
14.
DeweyJ (1927) The Public and Its Problems: An Essay in Political Inquiry. University Park, PA: The Pennsylvania State University Press.
15.
DeweyJ (1939) Theory of Valuation. Chicago, IL: The University of Chicago Press.
16.
EinsiedelEF (2000) Understanding ‘publics’ in the public understanding of science. In: DierkesMvon GroteC (eds) Between Understanding and Trust: The Public, Science and Technology. Amsterdam: Harwood Academic, pp. 205–215.
17.
EvansGDurantJ (1995) The relationship between knowledge and attitudes in the public understanding of science in Britain. Public Understanding of Science4(1): 57–74.
18.
FinchWH (2010) Imputation methods for missing categorical questionnaire data: A comparison of approaches. Journal of Data Science8(8): 361–378.
19.
FreudenburgWRPastorSK (1992) Public responses to technological risks: Toward a sociological perspective. The Sociological Quarterly33(3): 389–412.
20.
GauchatGW (2008) A test of three theories of anti-science attitudes. Sociological Focus41(4): 337–357.
21.
GauchatGW (2015) The political context of science in the United States: Public acceptance of evidence-based policy and science funding. Social Forces94(2): 723–746.
22.
GoodmanLA (2002) Latent class analysis: The empirical study of latent types. In: HagenaarsJAMcCutcheonAL (eds) Applied Latent Class Analysis. Cambridge: Cambridge University Press, pp. 3–55.
23.
GottweisH (2002) Gene therapy and the public: A matter of trust. Gene Therapy9(11): 667–669.
24.
GregoryJMillerS (1998) Science in Public: Communication, Culture, and Credibility. New York, NY: Plenum Press.
25.
GrossPRLevittN (1994) Higher Superstition: The Academic Left and its Quarrels with Science. Baltimore, MD: Johns Hopkins University Press.
26.
GuentherLWeingartP (2017) Promises and reservations towards science and technology among South African publics: A culture-sensitive approach. Public Understanding of Science27(1): 47–58.
27.
HapperCPhiloG (2013) The role of the media in the construction of public belief and social change. Journal of Social and Political Psychology1(1): 321–336.
28.
HitlinS (2003) Values as the core of personal identity: Drawing links between two theories of self. Social Psychology Quarterly66(2): 118–137.
29.
HitlinS (2006) Parental influences on children’s values and aspirations: Bridging two theories of social class and socialization. Sociological Perspectives49(1): 25–46.
30.
HitlinSPiliavinJA (2004) Values: Reviving a dormant concept. Annual Review of Sociology30: 359–393.
31.
HoltonG (1993) Science and Anti-Science: Purity and Power in Modern Knowledge. Cambridge, MA: Harvard University Press.
32.
InglehartRWelzelC (2005) Modernization, Cultural Change, and Democracy: The Human Development Sequence. Cambridge: Cambridge University Press.
33.
InglehartRWelzelC (2010) Changing mass priorities: The link between modernization and democracy. Perspectives on Politics8(2): 551–567.
34.
InglehartRHaerpferCMorenoAWelzelCKizilovaKDiez-MedranoJet al. (2014) World Values Survey: Round Six – Country-Pooled Datafile 2010–2014. Madrid: JD Systems Institute.
35.
IrwinAMichaelM (2003) Science, Social Theory and Public Knowledge. London: McGraw-Hill Education.
36.
JohnsonDRScheitleCPEcklundEH (2015) Individual religiosity and orientation towards science: Reformulating relationships. Sociological Science2: 106–124.
37.
KawamotoSNakayamaMSaijoM (2013) Using a scientific literacy cluster to determine participant attitudes in scientific events in japan, and potential applications to improving science communication. Journal of Science Communication12(1): 1–12.
38.
KemanHPenningsP (2017) Comparative research methods. In: CaramaniD (ed.) Comparative Politics. London: Oxford University Press, pp. 49–63.
39.
KvaløyBFinseraasHListhaugO (2012) The publics’ concern for global warming: A cross-national study of 47 countries. Journal of Peace Research49(1): 11–22.
40.
LakatosZ (2015) Traditional values and the Inglehart constructs. Public Opinion Quarterly79(Suppl. 1): 291–324.
41.
LoAY (2016) National income and environmental concern: Observations from 35 countries. Public Understanding of Science25(7): 873–890.
42.
Lü (2009) The value of the use of biotechnology: Public views in China and Europe. Public Understanding of Science18(4): 481–492.
43.
MacnaghtenPChilversJ (2014) The future of science governance: Publics, policies, practices. Environment and Planning C: Politics and Space32(3): 530–548.
44.
MillerJD (1983) The American People and Science Policy: The Role of Public Attitudes in the Policy Process. Elmsford, NY: Pergamon Press.
45.
MuellerSCBakhirevABöhmMSchröerMKrcmarHWelpeIM (2017) Measuring and mapping the emergence of the digital economy: A comparison of the market capitalization in selected countries. Digital Policy, Regulation and Governance19(5): 367–382.
NewmanBJJohnstonCDLownL (2015) False consciousness or class awareness? Local income inequality, personal economic position, and belief in American meritocracy. American Journal of Political Science59(2): 326–340.
49.
NylundKLAsparouhovTMuthénBO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal14(4): 535–569.
50.
OkamuraK (2016) Dynamic development of public attitudes towards science policymaking. Public Understanding of Science25(4): 465–479.
51.
Organisation for Economic Co-Operation and Development (OECD) (2013) OECD Skill Outlook 2013: First Results from the Survey of Adult Skills. Paris: OECD.
52.
Organisation for Economic Co-Operation and Development (OECD) (2015a) OECD Science, Technology and Industry Scoreboard 2015: Innovation for Growth and Society. Paris: OECD. Available at: http://dx.doi.org/10.1787/sti_scoreboard-2015-en
53.
Organisation for Economic Co-Operation and Development (OECD) (2015b) Students, Computers and Learning: Making the Connection. Paris: OECD.
54.
Organisation for Economic Co-Operation and Development (OECD) (2016) Education at a Glance: 2015 Indicators. Paris: OECD.
55.
ParboteeahKPAddaeHMCullenJB (2012) Propensity to support sustainability initiatives: A cross-national model. Journal of Business Ethics105(3): 403–413.
56.
PetersMA (2007) Knowledge Economy, Development and the Future of Higher Education. New York, NY: Sense Publishers.
57.
PetterssonTEsmerY (2008) Changing Values, Persisting Cultures: Case Studies in Value Change. London: Brill.
58.
PielkeRA (2007) The Honest Broker: Making Sense of Science in Policy and Politics. New York, NY: Cambridge University Press.
59.
ReyesJAL (2015) Cross-section analyses of attitudes towards science and nature from the International Social Survey Programme 1993, 2000, and 2010 surveys. Public Understanding of Science24(3): 338–357.
60.
Rodríguez-PoseAWilkieC (2016) Putting China in perspective: A comparative exploration of the ascent of the Chinese knowledge economy. Cambridge Journal of Regions, Economy and Society9(3): 479–497.
61.
RokeachM (1968) Beliefs, Attitudes and Values: A Theory of Organization and Change. San Francisco, CA: Milton.
62.
RousselièreDRousselièreS (2016) Decomposing the effects of time on the social acceptability of biotechnology using age-period-cohort-country models. Public Understanding of Science26(6): 650–670.
63.
ScheufeleDACorleyEAShihTJDalrympleKEHoSS (2009) Religious beliefs and public attitudes toward nanotechnology in Europe and the United States. Nature Nanotechnology4(2): 91–94.
64.
SchwartzSHBilskyW (1990) Toward a theory of the universal content and structure of values: Extensions and cross-cultural replications. Journal of Personality and Social Psychology58(5): 878–891.
65.
SheinPPLiYYHuangTC (2015) The four cultures: Public engagement with science only, art only, neither, or both museums. Public Understanding of Science24(8): 943–956.
66.
StavrovaOEhlebrachtDFetchenhauerD (2016) Belief in scientific-technological progress and life satisfaction: The role of personal control. Personality and Individual Differences96: 227–236.
67.
TeinJYCoxeSChamH (2013) Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling: A Multidisciplinary Journal20(4): 640–657.
68.
TeoT (2008) Assessing the computer attitudes of students: An Asian perspective. Computers in Human Behavior24(4): 1634–1642.
Van DijckJ (2003) After the ‘two cultures’: Toward a ‘(multi)cultural’ practice of science communication. Science Communication25(2): 177–190.
71.
VermuntJK (2010) Latent class modeling with covariates: Two improved three-step approaches. Political Analysis18(4): 450–469.
72.
VinovskisM (2015) From a Nation at Risk to No Child Left behind: National Education Goals and the Creation of Federal Education Policy. New York, NY: Teachers College Press.
73.
Von RotenFC (2004) Gender differences in attitudes toward science in Switzerland. Public Understanding of Science13(2): 191–199.
74.
WelzelCDaltonR (2017) Cultural change in Asia and beyond: From allegiant to assertive citizens. Asian Journal of Comparative Politics2(2): 112–132.
75.
World Values Survey (WVS) (2016) World Values Survey, Wave 6 (2010–2014). Madrid: ASEP/JDS.
76.
WynneB (1992) Public understanding of science research: New horizons or hall of mirrors?Public Understanding of Science1(1): 37–43.
77.
XuDDronkersJ (2016) Migrant children in Shanghai: A research note on the PISA-Shanghai controversy. Chinese Sociological Review48(3): 271–295.
78.
ZengZ (2009) The comparison of innovation activities and international trade effect in China and Japan in the era of knowledge economy. Journal of Chinese Economic and Foreign Trade Studies2(3): 211–228.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
