Better but still biased: Analytic cognitive style and belief bias

Belief bias is the tendency for prior beliefs to influence people's deductive reasoning in two ways: through the application of a simple belief-heuristic (response bias) and through the application of more effortful reasoning for unbelievable conclusions (accuracy effect or motivated reasoning). Previous research indicates that cognitive ability is the primary determinant of the effect of beliefs on accuracy. In the current study, we show that the mere tendency to engage analytic reasoning (analytic cognitive style) is responsible for the effect of cognitive ability on motivated reasoning. The implications of this finding for our understanding of the impact of individual differences on belief bias are discussed

Beliefs About COVID-19 in Canada, the United Kingdom, and the United States: A Novel Test of Political Polarization and Motivated Reasoning

What are the psychological consequences of the increasingly politicized nature of the COVID-19 pandemic in the United States relative to similar Western countries? In a two-wave study completed early (March) and later (December) in the pandemic, we found that polarization was greater in the United States (N = 1,339) than in Canada (N = 644) and the United Kingdom. (N = 1,283). Political conservatism in the United States was strongly associated with engaging in weaker mitigation behaviors, lower COVID-19 risk perceptions, greater misperceptions, and stronger vaccination hesitancy. Although there was some evidence that cognitive sophistication was associated with increased polarization in the United States in December (but not March), cognitive sophistication was nonetheless consistently negatively correlated with misperceptions and vaccination hesitancy across time, countries, and party lines. Furthermore, COVID-19 skepticism in the United States was strongly correlated with distrust in liberal-leaning mainstream news outlets and trust in conservative-leaning news outlets, suggesting that polarization may be driven by differences in information environments

Displaying News Source Trustworthiness Ratings Reduces Sharing Intentions for False News Posts

Professional fact-checking of individual news headlines is an effective way to fight misinformation, but it is not easily scalable, because it cannot keep pace with the massive speed at which news content gets posted on social media. Here we provide evidence for the effectiveness of ratings of news sources, instead of individual news articles. In a large pre-registered experiment with quota-sampled Americans, we find that participants are less likely to share false headlines (and more discerning of true versus false headlines) when 1-to-5 star trustworthiness ratings were applied to news headlines. This is true both when the ratings are generated by fact-checkers and by laypeople (although the effect is stronger using fact-checker ratings). We also observe a positive spillover effect: sharing discernment also increases for headlines whose source was not rated, likely because the presence of ratings on some headlines prompts users to reflect on source quality more generally. This study suggests that displaying information regarding the trustworthiness of news sources provides a scalable approach for reducing the spread of low-quality information

Differences in misinformation sharing can lead to politically asymmetric sanctions

In response to intense pressure, technology companies have enacted policies to combat misinformation1–4. The enforcement of these policies has, however, led to technology companies being regularly accused of political bias5–7. We argue that differential sharing of misinformation by people identifying with different political groups8–15 could lead to political asymmetries in enforcement, even by unbiased policies. We first analysed 9,000 politically active Twitter users during the US 2020 presidential election. Although users estimated to be pro-Trump/conservative were indeed substantially more likely to be suspended than those estimated to be pro-Biden/liberal, users who were pro-Trump/conservative also shared far more links to various sets of low-quality news sites—even when news quality was determined by politically balanced groups of laypeople, or groups of only Republican laypeople—and had higher estimated likelihoods of being bots. We find similar associations between stated or inferred conservatism and low-quality news sharing (on the basis of both expert and politically balanced layperson ratings) in 7 other datasets of sharing from Twitter, Facebook and survey experiments, spanning 2016 to 2023 and including data from 16 different countries. Thus, even under politically neutral anti-misinformation policies, political asymmetries in enforcement should be expected. Political imbalance in enforcement need not imply bias on the part of social media companies implementing anti-misinformation policies

Sub-Angstrom Microscopy Through Incoherent Imaging and Image Reconstruction

Z-contrast scanning transmission electron microscopy (STEM) with a high-angle annular detector breaks the coherence of the imaging process, and provides an incoherent image of a crystal projection. Even in the presence of strong dynamical diffraction, the image can be accurately described as a convolution between an object function, sharply peaked at the projected atomic sites, and the probe intensity profile. Such an image can be inverted intuitively without the need for model structures, and therefore provides the important capability to reveal unanticipated interfacial arrangements. It represents a direct image of the crystal projection, revealing the location of the atomic columns and their relative high-angle scattering power. Since no phase is associated with a peak in the object function or the contrast transfer function, extension to higher resolution is also straightforward. Image restoration techniques such as maximum entropy, in conjunction with the 1.3 A probe anticipated for a 300 kV STEM, appear to provide a simple and robust route to the achievement of sub-Angstrom resolution electron microscopy

The impact of overseas training on curriculum innovation and change in English language education in Western China

This article assesses the impact of a UK-based professional development programme on curriculum innovation and change in English Language Education (ELE) in Western China. Based on interviews, focus group discussions and observation of a total of 48 English teachers who had participated in an overseas professional development programme influenced by modern approaches to education and ELE, and 9 of their colleagues who had not taken part, it assesses the uptake of new approaches on teachers’ return to China. Interviews with 10 senior managers provided supplementary data. Using Diffusion of Innovations Theory as the conceptual framework, we examine those aspects of the Chinese situation that are supportive of change and those that constrain innovation. We offer evidence of innovation in classroom practice on the part of returnees and ‘reinvention’ of the innovation to ensure a better fit with local needs. The key role of course participants as opinion leaders in the diffusion of new ideas is also explored. We conclude that the selective uptake of this innovation is under way and likely to be sustained against a background of continued curriculum reform in China

Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media

When users on social media share content without considering its veracity, they may unwittingly be spreading misinformation. In this work, we investigate the design of lightweight interventions that nudge users to assess the accuracy of information as they share it. Such assessment may deter users from posting misinformation in the first place, and their assessments may also provide useful guidance to friends aiming to assess those posts themselves. In support of lightweight assessment, we first develop a taxonomy of the reasons why people believe a news claim is or is not true; this taxonomy yields a checklist that can be used at posting time. We conduct evaluations to demonstrate that the checklist is an accurate and comprehensive encapsulation of people's free-response rationales. In a second experiment, we study the effects of three behavioral nudges -- 1) checkboxes indicating whether headings are accurate, 2) tagging reasons (from our taxonomy) that a post is accurate via a checklist and 3) providing free-text rationales for why a headline is or is not accurate -- on people's intention of sharing the headline on social media. From an experiment with 1668 participants, we find that both providing accuracy assessment and rationale reduce the sharing of false content. They also reduce the sharing of true content, but to a lesser degree that yields an overall decrease in the fraction of shared content that is false. Our findings have implications for designing social media and news sharing platforms that draw from richer signals of content credibility contributed by users. In addition, our validated taxonomy can be used by platforms and researchers as a way to gather rationales in an easier fashion than free-response.Comment: To appear in CSCW'2