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AbstractProfessor Nicholas (Nick) Martin spearheaded initial investigations into the genetic basis of political attitudes and behaviors, demonstrating that behaviors that are perceived as socially constructed could have a biological basis. As he showed, the typical mode of inheritance for political attitudes consists of approximately equal proportions of variance from additive genetic, shared environmental and unique environmental sources. This differs from other psychological variables, such as personality traits, which tend to be characterized by genetic and unique environmental sources of variation. By treating political attitudes as a model phenotype, Nick Martin was able to leverage the unique pattern of observed intergenerational transmission for political attitudes to reexamine the quintessential assumptions of the classical twin model. Specifically, by creatively leveraging the nuances of the genetic architecture of political attitudes, he was able to demonstrate the robustness of the equal environments assumption and suggest corrections to account for assortative mating. These advances have had a substantial impact on both the fields of political science, as well as behavioral and quantitative genetics.

Traditional theories of political participation have emphasized its social and normative components; however, recent evidence suggests that political participation has a strong additive genetic component. Accordingly, it is necessary to reevaluate the traditional empirical findings and begin to integrate the two approaches. To do so, a variety of analyses were conducted that explore the modes of genetic and environmental transmission. I find that the empirical estimates of the relationships between the phenotypic level traits are highly consistent with what has been found in the traditional literature, the vast majority of the variance in political participation that is accounted for by the predictor variables is being accounted for at the genetic level, and not at the environmental level. Thus, the current findings suggest that the empirical results found in prior studies are quite likely very accurate. However, the interpretation of those empirical findings, as well as the subsequent theoretical implications, require serious revision.

Traditional theories of political participation have emphasized its social and normative components; however, recent evidence suggests that political participation has a strong additive genetic component. Accordingly, it is necessary to reevaluate the traditional empirical findings and begin to integrate the two approaches. To do so, a variety of analyses were conducted that explore the modes of genetic and environmental transmission. I find that the empirical estimates of the relationships between the phenotypic level traits are highly consistent with what has been found in the traditional literature, the vast majority of the variance in political participation that is accounted for by the predictor variables is being accounted for at the genetic level, and not at the environmental level. Thus, the current findings suggest that the empirical results found in prior studies are quite likely very accurate. However, the interpretation of those empirical findings, as well as the subsequent theoretical implications, require serious revision.

The authors regret that the coding of the attitude items in the manuscript 'Using genetic information to test causal relationships in cross-sectional data' was exactly reversed. The codebook that we were working from for the original paper was the opposite of the actual coding of the raw variables. The purpose of the paper was to present an empirical model for testing causal hypotheses using cross-sectional twin data. The data were used to present readers with an example of how to use the method. Accordingly, the impact of the coding error on the conclusions is minimal. Of course, this has the potential to cause confusion for individuals who are focused on the sign of the relationship between personality and sex attitudes and not on the causal structure.

Cross-sectional data from twins contain information that can be used to derive a test of causality between traits. This test of directionality is based upon the fact that genetic relationships between family members conform to an established structural pattern. In this paper we examine several common methods for empirically testing causality as well as several genetic models that we build on for the Direction of Causation (DoC) model. We then discuss the mathematical components of the DoC model and highlight limitations of the model and potential solutions to these limitations. We conclude by presenting an example from the personality and politics literature that has begun to explore the question whether or not personality traits cause people to hold specific political attitudes.

Cross-sectional data from twins contain information that can be used to derive a test of causality between traits. This test of directionality is based upon the fact that genetic relationships between family members conform to an established structural pattern. In this paper we examine several common methods for empirically testing causality as well as several genetic models that we build on for the Direction of Causation (DoC) model. We then discuss the mathematical components of the DoC model and highlight limitations of the model and potential solutions to these limitations. We conclude by presenting an example from the personality and politics literature that has begun to explore the question whether or not personality traits cause people to hold specific political attitudes. [Reprinted by permission of Sage Publications Ltd., copyright holder.]

Cross-sectional data from twins contain information that can be used to derive a test of causality between traits. This test of directionality is based upon the fact that genetic relationships between family members conform to an established structural pattern. In this paper we examine several common methods for empirically testing causality as well as several genetic models that we build on for the Direction of Causation (DoC) model. We then discuss the mathematical components of the DoC model and highlight limitations of the model and potential solutions to these limitations. We conclude by presenting an example from the personality and politics literature that has begun to explore the question whether or not personality traits cause people to hold specific political attitudes.

ABSTRACTClaims of misconduct must be accompanied by verifiable proof. In "Diagnosis versus Ideological Diversity," Phillip W. Gray (2019) professes the need to address bias and dishonesty in research but contradicts his stated goals by making untrue and unsupported allegations of misconduct. He equates a coding error with LaCour and Green's (2014) suspected data fabrication while disregarding publicly available contradictory evidence. In this evidence-based article, we demonstrate that Gray made a series of false accusations of research dishonesty and ideological bias. His assertions not only are unsupported; the evidence also shows the opposite. PS: Political Science & Politics edited Gray's article after publication and online distribution—removing or modifying the most explicitly false and harmful statements—and changed his central thesis but without changing the DOI. This resulted in two different articles with the same DOI. Although retraction is uncommon, this degree of post-publication modification appears to meet the threshold. The published corrigendum failed to address Gray's false allegations, pervasive and unsubstantiated insinuations of misconduct, and errors that persist in the second edition of his article. The constellation of behaviors by the journal and Gray contradicts academic norms and emphasizes the need to establish clear standards of evidence when making accusations of academic misconduct.

In this article, we respond to Shultziner's critique that argues that identical twins are more alike not because of genetic similarity, but because they select into more similar environments and respond to stimuli in comparable ways, and that these effects bias twin model estimates to such an extent that they are invalid. The essay further argues that the theory and methods that undergird twin models, as well as the empirical studies which rely upon them, are unaware of these potential biases. We correct this and other misunderstandings in the essay and find that gene-environment (GE) interplay is a well-articulated concept in behavior genetics and political science, operationalized as gene-environment correlation and gene-environment interaction. Both are incorporated into interpretations of the classical twin design (CTD) and estimated in numerous empirical studies through extensions of the CTD. We then conduct simulations to quantify the influence of GE interplay on estimates from the CTD. Due to the criticism's mischaracterization of the CTD and GE interplay, combined with the absence of any empirical evidence to counter what is presented in the extant literature and this article, we conclude that the critique does not enhance our understanding of the processes that drive political traits, genetic or otherwise.

Der Beitrag untersucht die kognitiven Verarbeitungsstile von Individuen während emotionaler Phasen und stellt eine Verknüpfung her zu der Art und Weise, wie Politikwissenschaft üblicherweise mit der Messung und Bewertung von Emotionen umgeht. Zunächst widmet sich der Beitrag der Unterscheidung zwischen Emotion und Affekt sowie den Modellen der Informationsverarbeitung. Anschließend geht es um den direkten Einfluss positiver und negativer affektiver Zustände auf das Verhalten und auf Beurteilungen. Konzepte und Modelle zu den Einflüssen von Affekten und Emotionen werden vorgestellt und schließlich auf die Messung und die politikwissenschaftliche Forschung in Bezug auf Emotionen eingegangen. (ICB2).