Public Understanding of Science最新文献

From disputes over COVID-19 to contestation over climate science, questions of the value and legitimacy of mainstream scientific knowledge have become matters of high-stakes political struggle. Here, we introduce a novel computational tool to identify and track the emergence, proliferation, and historical variations of discourses that either seek to invoke the authority of scientific expertise or to criticize scientific claims, institutions, and experts. We describe the tool's development, demonstrate its predictive and convergent validity, and illustrate its potential across three case studies shedding light on how elite rhetoric may drive political polarization around science in the United States. Among other findings, we find that political statements invoking scientific expertise have historically been more likely to receive coverage in mainstream American newspapers than statements that do not invoke expertise. However, this apparent advantage disappears over time, suggesting the discursive authority associated with the invocation of scientific methods, credentials, and institutions may be diminishing.

Admitting that one's research findings are wrong involves admitting a potential instance of incompetence, which can keep scientists from engaging in wrongness admission. However, wrongness admission can yield favorable perceptions. In five experiments (N = 2420), we tested whether wrongness admission yields higher perceived trustworthiness in the scientist and trust in science and discipline-specific research as well as public funding support for the scientist, science, and discipline-specific research. Scientists engaging in wrongness admission (vs refuse or do not comment) were perceived as more trustworthy and received more support for federal funding for their own research. Moreover, wrongness admission yielded similar levels of science and discipline-specific public funding support. Wrongness admission not only facilitated higher scientist trustworthiness, but trustworthiness was, in turn, associated with greater trust in science and psychology, as well as scientist and psychology public funding support. This work highlights potential benefits of scientist wrongness admission amidst failed replications.

Understanding how media influence public attitudes toward science during societal challenges is crucial for effective science communication. This study examines the role of media use and sociodemographic factors in shaping public attitudes toward science in Switzerland using panel data from three surveys over 6 years (N₂₀₁₆ = 1,051; N₂₀₁₉ = 339; N₂₀₂₂ = 122). Results show that media usage and sociodemographics influenced attitudes, especially during the COVID-19 pandemic. Lower education and stronger religiosity correlated with reduced interest in or trust in science. Use of online legacy media showed rally-around-the-flag effects, but we found no clear differences between public and private broadcasters regarding their impact on science attitudes. These findings highlight the relationship of media use, sociodemographics, and public attitudes during societal uncertainty and over time, offering insights for targeted, context-sensitive science communication.

Previous studies have examined the relationship between religion and science, but the role of secular belief systems in shaping attitudes toward scientific findings remains understudied. This research tested the leap of faith hypothesis, suggesting that secular individuals may accept scientific claims based more on faith in science than on scientific literacy. In Study 1 (N = 202) and a preregistered Study 2 (N = 300), Indonesian adults completed measures of secular beliefs, faith in science, scientific literacy, and confidence in scientific consensus. Across both studies, faith in science consistently mediated the effect of secular beliefs on confidence in scientific consensus, whereas scientific literacy did not. These findings suggest that secular individuals may place trust in scientific claims through conviction-indicating that confidence in science can operate as a faith-like commitment rather than a cognitive understanding.

The 1974 discovery of Lucy in Ethiopia marked a watershed moment in paleoanthropology. While the scientific community classifies Lucy as an extinct early hominin species that predates Homo sapiens by millions of years, in Ethiopia, she has been embraced as a national matriarch-the first human and mother of humanity. This commentary analyzes how government campaigns and media coverage actively promote a humanized, scientifically inaccurate identity for Lucy. By framing her as "one of us," these narratives sacrifice scientific facts for emotional resonance and commercial appeal. This popular mischaracterization creates significant obstacles for public science education and undermines scientific literacy, raising ethical questions about the role of the state and media in science communication. Ultimately, the article advocates for a balanced approach that celebrates Lucy's immense cultural and national importance without compromising the scientific integrity of human evolutionary science.

In this essay, we argue that the applications of generative-AI technologies to science communication need careful consideration to ensure such uses are desirable, and socially and ethically acceptable. In early applications of GenAI in science communication, especially in public media, there has been swift and overwhelmingly negative response to news about its use. Drawing on existing literature about generative-AI in adjacent fields to science communication, and on the scholarship on the ethics of science communication, this article maps out the key ethical issues that the use of generative-AI technologies raise for science communication. Specifically, acknowledging that generative-AI is more than an output-producing technology but is a constellation of governance, infrastructure, data, human and computing operating systems, we argue that three dimensions of ethical concerns need to be explored: the communication outputs of generative AI; the social and environmental impacts of using generative AI technologies in science communication and the narratives we tell about AI technology.

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.

Storytelling is a growing topic in science communication research, highlighting the importance of learning from existing storytelling research from other disciplines. Storytelling research in cultural evolution has identified a number of cognitive biases in how we transmit information: stories are remembered and passed on more faithfully when they contain social and survival information, negative information or counterintuitive information. In this article, we review this cultural evolution literature and present findings from a set of interviews with science communication professionals. We asked science communicators about the potential benefits and risks that may come about when using cognitive biases within science communication storytelling. Science communicators reported already using some cognitive biases in their practice. Participants also expressed concerns about some tactics that might contradict objectives of science communication, threaten the integrity of science and science communication and risk the welfare of audiences. We map the benefits and risks reported using a thematic analysis.

This article examines trust in science in England, focusing on variation across demographic and ideological groups. Using survey data from 11,173 respondents, we compare trust in two domains, medical doctors and scientists, to explore whether predictors operate similarly across these professional groups. We find higher education is associated with greater trust, while right-wing political orientation predicts lower trust. Religious affiliation also matters, with some faith groups reporting lower trust relative to the non-religious baseline. Gender differences emerge as well, particularly in trust in medical doctors. Respondents selecting 'Prefer not to say' on the religion item report significantly lower trust in both doctors and scientists, consistent with a broader privacy-motivated disclosure style. Our results highlight the importance of considering not just overall levels of trust in science, but variation across education, ideology, religion and gender, and they suggest that trust in doctors and trust in scientists, while related, are not interchangeable.

Intermediaries such as (digital) media use trust cues in their content, that is, information and linguistic markers that present public audiences reasons for trusting scientists, scientific organizations, and the science system. Trust cues refer to dimensions of trust in science such as expertise, integrity, benevolence, transparency, and dialogue. Because digital media environments are expected to be heterogeneous in content, the sources of trust cues, characteristics of objects of trust in science (e.g. the gender of scientists), and their impact on public trust in science may vary. In our quantitative content analysis, we identified trust cues across several sources of scientific information (n = 906) and examined their heterogeneity in digital media environments. Our results reveal journalism as the most important source for trust cues and that scientists are the most prevalent object of trust-with female scientists being underrepresented. Differences across (digital) media imply varying impacts on public trust in science.