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

The positive association of education with the trust in science and scientists is weaker in highly corrupt countries

One of the most prominent correlates of trust in science and scientists is education level, possibly because educated individuals have higher levels of science knowledge and thinking ability, suggesting that trusting science and scientists relies more on reflective thinking abilities. However, it is relatively more reasonable for highly educated individuals to suspect authority figures in highly corrupt countries. We tested this prediction in two nationally representative and probabilistic cross-cultural data sets (Study 1: 142 countries, N = 40,085; Study 2: 47 countries, N = 69,332), and found that the positive association between education and trust in scientists (Study 1) and science (Study 2) was weaker or non-existent in highly corrupt countries. The results did not change after statistically controlling for age, sex, household income, and residence. We suggest future research to be more considerate of the societal context in understanding how education status correlates with trust in science and scientists.

Who engages with science, and how? An empirical typology of Europeans' science engagement

This article seeks to expand the literature on science attitudes by developing an empirical typology of people's engagement choices and investigating their sociodemographic characteristics. Public engagement with science is gaining a central role in current studies of science communication, as it implies a bidirectional flow of information, which makes science inclusion and knowledge co-production realizable goals. However, research has produced few empirical explorations of the public's participation in science, especially considering its sociodemographic characteristics. By means of segmentation analysis using Eurobarometer 2021 data, I observe that Europeans' science participation can be distinguished into four types, disengaged, the largest group, aware, invested, and proactive. As expected, descriptive analysis of the sociocultural characteristics of each group suggests that disengagement is most common among people with lower social status. In addition, in contrast to the expectations from existing literature, no behavioral distinction emerges between citizen science and other engagement initiatives.

A comparative study of the acceptance and understanding of evolution between China and the US

Prior work has found that Americans' views on evolution are significantly and positively related to their understanding of this theory. However, whether this relationship is cross-culturally robust is unknown. This article extends earlier work by measuring and comparing the acceptance and understanding of evolution among highly educated individuals in China and the United States. We find a significantly higher evolution acceptance level in the Chinese sample than in the US sample, but no significant difference in their average levels of evolution knowledge. Our analysis also shows that accepting evolutionary theory is related to understanding in both the US and the Chinese samples. These results provide evidence for the robustness of the relationship between understanding and acceptance of evolution across different cultural contexts. To our knowledge, this is the first attempt to comprehensively test understanding of evolutionary theory within a Chinese sample and to compare these results with the US sample.

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

Science communication scholars are publishing more and more segmentation analyses as they further our understanding of different audiences and their characteristics. They follow different aims, are therefore difficult to compare and do not lend themselves to more generalisable and theoretical knowledge production. Our field has the potential to follow a demand for more systematic efforts by taking advantage of our high-quality representative data sets focusing on public perceptions of science. Beforehand, however, science communication scholars using segmentation analyses have to identify common goals and overcome a number of hurdles concerning variable selection, methodological approaches, and transparency. Ultimately, a collaborative and systematic application of segmentation analyses could result in truly relevant insights for our field.