Politics and the Life Sciences最新文献

Taking insights from the fields of psychology and biology, a growing body of scholarship considers the psychophysiological foundations of political attitudes. Subconscious emotional reactions to threat, for example, have been shown to predict socially conservative attitudes toward out-groups. However, many of these studies fail to consider different sources of perceived threat. Using a combination of survey and physiological data, I distinguish between fear of others and fear of authority, finding that threat sensitivity predicts divergent political attitudes depending on the strength of each. Those who are more sensitive to threat from others tend to hold socially conservative attitudes, while those who fear authority generally take more libertarian positions. As sensitivity to threat is at least partially inherited, these findings highlight the genetic role of political predispositions.

In this article, we examine whether there is genetic overlap between personality traits and political participation, interest, and efficacy. We make several contributions to the literature. First, we use new data from a large sample of twins from Denmark to examine the link between genes, the Big Five traits, and political behavior. Previous research in this area has not examined the Danish context. Second, because our measures have some overlap with those used in previous studies, we are able to examine whether previous findings replicate in a different sample. Finally, we extend the literature by examining the possible genetic link between some personality and political traits that have not yet been explored. Overall, we find that genes account for a fairly large share of the correlation between two of the Big Five personality traits (openness and extraversion), political participation, and political interest. Thus, most of the relationship between these personality traits and our measures of political behavior can be accounted for by a common underlying genetic component.

This research letter introduces readers to health intelligence by conceptualizing critical components and providing a primer for research within political science broadly considered. Accordingly, a brief review of the literature is provided, concluding with possible future research agendas. The aim is to elaborate on the importance of public health intelligence to national security studies, and to political science more generally.

In recent decades, political psychologists have given a lot of attention to the role of emotions in politics. While there have been several different research programs, the dominant paradigm has been set by affective intelligence theory (AIT), developed by George Marcus, Russell Neuman, and Michael Mackuen. AIT has helped explain many puzzles in understanding how emotions influence political decisions, as any good paradigm should. At the same time, I argue it has also had the effect of limiting broader research into the range of discrete emotions, especially contempt. While recognizing the value of AIT, I call for more research that goes beyond its boundaries, showing through several recent studies how a focus on the additional effects of contempt can improve our understanding of voter decision-making.

Recent research contends that the behavioral immune system, operating largely outside conscious awareness, motivates individuals to exhibit higher levels of prejudice toward unfamiliar out-groups. This research finds that individual variance in disgust sensitivity correlates with support for political policies that facilitate the avoidance of out-groups. We were interested in developing less intrusive indicators of disgust sensitivity via olfactory measures (i.e., ratings of disgusting odors) and behavioral measures (e.g., willingness to touch disgusting objects) and studying the association between measures of disgust sensitivity and in-group bias among children and adults. We submitted a registered report to conduct this research and received an in-principle acceptance. Unfortunately, unforeseen events impaired our data collection, leaving us with a limited sample (n_children = 32, n_adults = 29) and reducing our ability to draw reliable conclusions from our results. In this essay, we describe our motivation and plan of research, the events that made completing the research impossible, and our preliminary results. In doing so, we hope to offer support for studying the effects of the behavioral immune system, even in ways that we did not originally plan. We conclude with a reflection on the value of registered reports for advancing science.

Pre-registration has become an increasingly popular proposal to address concerns regarding questionable research practices. Yet preregistration does not necessarily solve these problems. It also causes additional problems, including raising costs for more junior and less resourced scholars. In addition, pre-registration restricts creativity and diminishes the broader scientific enterprise. In this way, pre-registration neither solves the problems it is intended to address, nor does it come without costs. Pre-registration is neither necessary nor sufficient for producing novel or ethical work. In short, pre-registration represents a form of virtue signaling that is more performative than actual.

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter's standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter's API version 2.

Tasks driven by artificial intelligence (AI), such as evaluating video job interviews, rely on facial recognition systems for decision-making. Therefore, it is extremely important that the science behind this technology is continually advancing. If not, visual stereotypes, such as those associated with facial age and gender, will lead to dangerous misapplications of AI.