Researching multiple publics through latent profile analysis: Similarities and differences in science and technology attitudes in China, Japan, South Korea and the United States

Abstract

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.

Science communication scholars use more and more segmentation analyses: Can we take them to the next level?

“…In line with this efforts towards a joint, or at least more explicit and ideally standardized, theoretical framework for variable selection, segmentation analyses in science communication should also aim to strengthen their methodological approach. Current analyses have employed almost all the most common statistical techniques for clustering data, ranging from distanced-based procedures like hierarchical (Runge et al, 2018) and k-means clustering (Ipsos MORI, 2013) to model-based procedures like latent class (Schäfer et al, 2018) and latent profile analysis (Pullman et al, 2018), sometimes with running a factor analysis in a first step (Kawamoto et al, 2011) and sometimes without (Guenther & Weingart, 2017). Other studies did not employ multivariate statistics at all and applied "manual clustering" by defining which combinations of variable expressions would lead to which kind of segment (Cámara et al, 2018;Nisbet & Markowitz, 2014;Sweeney Research, 2011).…”

“…Most of these studies do not aim to build a body of systematic knowledge but have more practical aims and, therefore, are not motivated by a common set of goals and are also less theoretically-driven. Some studies heavily focus on country comparisons (Pullman et al, 2018), some on temporal developments within the same country (Okamura, 2016), whereas others aim to improve science communication efforts in general (Schäfer et al, 2018), to recruit potential citizen scientists (Füchslin, Schäfer, & Metag, 2019), to increase people's scientific literacy (Kawamoto et al, 2011), or by offering efficient "post-hoc" segmentations (Runge, Brossard, & Xenos, 2018). Against this backdrop, Scheufele (2018) recently demanded that fields like science and environmental communication strive for more systematic segmentation efforts, taking into account differences between issues, issue cycles, cultural or national contexts, and methodological approaches.…”

“…Lastly, a fourth level pertains to the differences in variable measurement, both in wording and scale. This leads to cases where three different studies assess whether people agree that "science improves our lives" by applying four-, five-, or ten-point scales, respectively, and using three (albeit slightly) different wordings (Nisbet & Markowitz, 2014;Pullman et al, 2018;Schäfer et al, 2018).…”

“…Some authors label very similar items with different dimensions or assign them to a broad category like "attitudes towards science". Many prior analyses could have followed the already mentioned categorisation proposed by Schäfer et al (2018): Pullman et al (2018) would have covered hopes and reservations towards science as well as the subjective norm regarding informational behaviour. Besley (2018) included items that covered hopes and reservations as well as the cognitive dimension of attitudes towards science and technology.…”

“…Since then, however, more and more segmentation analyses were published in research journals like Public Understanding of Science (PUS), Environmental Communication and the Journal of Science Communication . Just recently, PUS was part of a burst of segmentations starting in 2016, including analyses for South Africa (Guenther and Weingart, 2017), Switzerland (Schäfer et al, 2018), Japan (Okamura, 2016) as well as China, South Korea and the United States (Pullman et al, 2018). Complementing this burst, a special issue on ‘Audience Segments in Environmental and Science Communication’ was published in Environmental Communication (Metag and Schäfer, 2018).…”