Public Understanding of Science最新文献

Substantial minorities of the population report a low degree of trust in science, or endorse conspiracy theories that violate basic scientific knowledge. This might indicate a wholesale rejection of science. In four studies, we asked 782 US participants questions about trust in science, conspiracy beliefs, and basic science (e.g. the relative size of electrons and atoms). Participants were provided with the scientifically consensual answer to the basic science questions, and asked whether they accept it. Acceptance of the scientific consensus was very high in the sample as a whole (95.1%), but also in every sub-sample (e.g. no trust in science: 87.3%; complete endorsement of flat Earth theory: 87.2%). This quasi-universal acceptance of basic science suggests that people are motivated to reject specific scientific beliefs, and not science as a whole. This could be leveraged in science communication.

This study used a survey (n = 1897) of United States- and Canada-based scientists in six scientific fields to explore correlates of perceived (a) public engagement goal importance and (b) personal goal prioritization. Building on the Integrated Behavioral Model, the results suggest that scientists' beliefs about the societal benefits of a goal (i.e. attitudes) are the most consistent predictors of goal importance ratings and personal goal prioritization. Other beliefs are also associated with personal goal prioritization, including beliefs about personal benefits, agency (i.e. self-efficacy), and to a lesser extent, social norms. The data further suggests that basic scientists have similar goals to applied scientists who were in the sample, and that there are few differences across the six fields studied. The conclusion is that proponents of specific behavioral goals may wish to focus on communicating the benefits of goals to scientists, more so than norms or efficacy.

Mounting socio-environmental crises have prompted calls for post-normal sustainability science, emphasising complexity, uncertainty, and epistemic pluralism, and framing science communication as dialogical and reflexive. However, previous research has identified a gap between these ideals and actual practices, where conventional norms of objectivity and expert authority often prevail. Drawing on Irwin's (2021) framework of socio-technical orders of thinking, we analyse interviews with 12 leading Danish sustainability scientists. Our thematic analysis shows that scientists pragmatically navigate between first-order (expert-led), second-order (inclusive), and third-order (reflexive and power-aware) modes of thinking. While third-order thinking emerges as integral to sustainability science, traditional assumptions about authority and neutrality continue to shape scientists' communication practices. These findings invite science communication scholars to view sustainability science as a fertile ground for developing and testing pluralistic, reflexive, and power-aware communication models, while also learning from the situated practices of scientists who already navigate these complexities in context.

We describe a focus group study of public perceptions of "deepfake" technology, that is, digitally manipulated videos that show people saying or doing things they never really did. The study was designed to explore the relationship between degree of closeness to or familiarity with technology and attitudes toward it. We find that in this case, publics that are closer have more positive and nuanced attitudes. In such cases, at least, it appears that distance does not lend enchantment. We suggest why this may be the case and propose further related research designed to test the conclusions reached here.

The study examines the intersection of science and politics by analyzing the involvement of N = 205 U.S. and N = 174 German scientists in policy disputes during the COVID-19 pandemic. I investigate how scientists integrate themselves into policy disputes. Through a survey, I identify four groups of scientists with specific self-images regarding their roles in policy disputes: Moderate Mainstreamers, Issue Advisors, Issue Advocates, and Honest Brokers. Furthermore, the findings reveal differences in how these groups of scientists perceive the importance of science in policy-making: Particularly U.S.-based Issue Advocates wish for science to direct policy-making. In addition, I find that pandemic researchers overwhelmingly do not support political causes by selectively communicating political advice. I present empirically evidence that pandemic researchers sought to clarify the relevance of research during the pandemic, but did not attempt to distort policy disputes dishonestly.

US conservatives are often seen as distrusting scientists, and liberals as more trusting. This article examines how alignment between an expert's field and individual political ideology affects claims perceptions. US adults (N = 1054) participated in a pre-registered (https://osf.io/9wnm2) online experiment, indicating their trust in five experts and evaluating the accuracy of four claims. Claims were attributed to experts from impact fields (focused on the consequences of industry and policy), production fields (industry-focused), scientists in general, or no source. Results show that liberals trust all experts more than conservatives and generally perceive claims as more accurate. However, the trust gap between liberals and conservatives is smaller for production experts. While no difference was found between the perceived accuracy of claims attributed to production versus impact experts, expert attribution increased some claims' perceived accuracy. These findings reveal some political-ideology preferences and that attributing a claim to an expert can improve its perception.

Genes are increasingly understood to influence behavior. Research-generally conducted among convenience samples- has suggested that genetic influences tend to be perceived as playing a greater role in positive (e.g. prosocial) behaviors than in negative (e.g. antisocial) behaviors. Several potential bases for this asymmetry have been explored previously. We examined, in a U.S. sample, whether an asymmetry in genetic attributions between prosocial and antisocial behavior would be observed, and if so, what might help to explain it. Results revealed that the asymmetry did occur and appeared to be robustly mediated by an asymmetry between how "natural" prosocial and antisocial behavior are perceived to be. Genetic attributions were also lower on average when the individual was described as African American, especially as an African American man. These findings provide further evidence that genetic attributions are endorsed selectively, in ways that appear to reflect pre-existing psychological motivations and views about human nature.

Communicating uncertainties is central to science communication, yet evidence on its effects is inconclusive. In an online experiment with a quasi-representative sample in Austria (N = 1126), we investigated the effects of message (uncertainty type) and audience characteristics (science-specific attitudes/beliefs) as potential moderating factors on risk perception and policy support in the context of microplastic health effects. Uncertainty communication, specifically communicated lack of scientific consensus (consensus uncertainty), triggered lower risk perception (small effect), and indirectly decreased policy support through message credibility and risk perception. These negative effects were lower (and not statistically significant) when communicating the remaining knowledge gaps (deficient uncertainty). Beliefs about science as a debate were positively associated with risk perception, trust in scientists with policy support and preference for information about uncertain science with both. However, these audience characteristics did not moderate the effects of uncertainty communication. The results highlight the importance of considering uncertainty types in environmental and health risk communication.

This scoping review examines how uncertainty has been measured in science communication research, analyzing 58 studies published between 1976 and 2024. The review identified 68 uncertainty measures, categorized into three main types: (1) trait uncertainty, (2) state uncertainty, and (3) uncertainty discrepancy. While most measures demonstrated good internal reliability, evidence for the validity of scales was limited, particularly for newly developed scales. The analysis reveals significant fragmentation in measurement approaches and a concerning reliance on single-item and unidimensional measures given the complexity of the construct. Science communication research would benefit from more rigorous scale development, standardized measurement approaches, and cross-cultural validation of uncertainty scales.