Metaphors of positions, spectrums, perspectives, viewpoints, and polarization reflect the same model, which treats beliefs—and the people who hold them—as points in space. This model is deeply rooted in quantitative research methods and influential traditions of Continental philosophy, and it is evident in some qualitative research. It can suggest that deliberation is difficult and rare because many people are located far apart ideologically, and their respective positions can be explained as dependent variables of factors like personality, partisanship, and demographics. An (...) alternative model treats a given person’s beliefs as connected by reasons to form networks. People disclose the connections among their respective beliefs when they discuss issues. This model offers insights about specific cases, such as discussions conducted on two US college campuses, which are represented here as belief-networks. The model also supports a more optimistic view of the public’s capacity to deliberate. (shrink)

Metacognitive mental states are mental states about mental states. For example, I may be uncertain whether my belief is correct. In social discourse, an interlocutor’s metacognitive certainty may constitute evidence about the reliability of their testimony. For example, if a speaker is certain that their belief is correct, then we may take this as evidence in favour of their belief, or its content. This paper argues that, if metacognitive certainty is genuine evidence, then it is disproportionate evidence for extreme beliefs. (...) In support of the argument, we report findings from five studies with different participant samples, designs, and measures. These studies show that, the more extreme an agent’s belief (positive or negative), the more certain they are about it, and vice versa. This relationship might contribute to moralism, virtue signalling, and polarisation, which in turn may be epistemically and morally problematic. Therefore, we caution against taking metacognitive certainty as genuine evidence. (shrink)

In social psychology, explicit and implicit attitudes play an important role for behavior prediction and explanation. Edouard Machery claims that attitudes are not mental states but dispositional character traits. The goal of this article is to show that this conceptualization of attitudes comes with two weaknesses: first, the author will show that if attitudes are traits, they are unmeasurable, or if we assume that a part of the trait is measurable, then we do not need the trait-picture, because then the (...) classic attitude-picture is sufficient. Second, it is unclear how the trait-picture leads to attitudes that explain behavior. (shrink)

Understanding and solving the psychological health problems of college students have become a focus of social attention. Complex networks have become important tools to study the factors affecting psychological health, and the Gaussian graphical model is often used to estimate psychological networks. However, previous studies leave some gaps to overcome, including the following aspects. When studying networks of subpopulations, the estimation neglects the intrinsic relationships among subpopulations, leading to a large difference between the estimated network and the real network. Because (...) of the high cost, previous psychological surveys often have a small sample size, and the psychological description is insufficient. Here, the intrinsic connections among multiple tasks are used, and multitask machine learning is applied to develop a multitask Gaussian graphical model. The psychological networks of the population and subpopulations are estimated based on psychological questionnaire data. This study is the first to apply a psychological network to such a large-scale college student psychological analysis, and we obtain some interesting results. The model presented here is a dynamic model based on complex networks which predicts individual behavior and provides insight into the intrinsic links among various symptoms. (shrink)