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This paper tests the degree to which Sunstein's law of group polarization predicts the increase or decrease in polarization among individuals in an out-group during a polarizing event. The authors use the discourse on Parler surrounding the events of January 6th as a case study.

The study includes an overall sentiment analysis, a statistical analysis of emotions, along with eight other feelings, including anger, anticipation, disgust, fear, joy, sadness, surprise and trust. Specifically, the authors measure the differences in feelings related language used in posts as they pertain to Donald Trump and the Make America Great Again (MAGA) movement vs. Trump's Vice President Mike Pence both before and after January 6, 2021. The authors use this empirical analysis to show whether polarization in the Parler community increased or decreased after January 6th.

The authors find evidence that there is more complexity to polarization than Sunstein's theory would predict. The authors would expect a very polarized outed group to become more polarized relative to the general public after a central event; however, the authors see two extremes emerging within the Parler community (both strongly positive and strongly negative feelings toward Trump). The authors do not see unanimous consent across the Parler platform as Sunstein's theory would suggest; the out-group is becoming more polarized relative to the rest of the population. Instead, the authors observe a wide mix in reactions. The results of this study demonstrate that there is dissent even among the Parler echo chamber. For many themes surrounding the January 6th riots, Parler users express strong disagreement with each other and a lack of unity in their feelings for former President Trump.

The results suggest further research into polarization of outed groups and the policy implications of their polarization changes over time.

Increases in group polarization are often a motivator for public policy and are further becoming a major focus for research. Brookings' authors Stephanie Forrest and Joshua Daymude point to polarization as a substantial threat to American society, claiming “reducing extreme polarization is key to stabilizing democracy” (2022). Researchers Diana Epstein and John D. Graham demonstrate that polarized politics has impacted the “substance of rulemaking, judicial decisions, and legislation” along with “complicating long-term policy changes” (2007). The authors study how entrepreneurs have responded to this increase in polarization and its implications for public policy.

Not only does group polarization impact all types of groups, from the social to the economic, but also it has “particular implications for insulated ‘outgroups’” (Sunstein, 1999, p. 21). Groups that are excluded by either coercion or choice from dialog with other groups become even more polarized and extreme (Sunstein, 1999; Turner et al., 1989).

The authors have engaged in an empirical analysis that no other paper has addressed. This paper summarized the Parler sample data set and analyzed various themes associated with the events of January 6th, namely President Trump and MAGA themes and Vice President Pence. The analysis demonstrated a dramatic increase in negative sentiment and emotion related to Vice President Mike Pence after January 6th as well as mixed support for President Trump and an increase in disgust before and after the Capitol riot.

This study aims to examine the mediating role played by corporate governance (CG) in the relationship between corporate social responsibility (CSR) and analyst forecast quality.

The authors raise three specific questions: Does CG play a mediating role in the relationship between CSR and analyst forecast quality? If so, is such mediation effect of CG reduced for firms with weak governance? Do firms with superior CSR performance experience higher analyst forecast quality through the mediation effect of CG?

The present results suggest that CG serves as a partial mediator that facilitates CSR’s positive influence on analyst forecast quality. However, further analyses show that in firms with a low governance score, CG does not have a mediation effect. Conversely, the authors find that firms with superior CSR performance have higher forecast quality through the mediation effect of CG. The authors also find that the mediation effect of CG is more pronounced for the environmental component than for the social component of CSR.

To the best of the authors’ knowledge, this study is the first to investigate the role of CG as a mediator between CSR and analyst forecast quality and to reveal that the strength of this effect varies depending on firms’ CG level and CSR commitment.

Post-merger integration (PMI) success depends heavily on the social and cultural integration of the two legacy organizations. Given that organizational members work and exchange information through social relationships, social network analysis can serve as a useful tool to identify key actors, address areas of concern, and measure PMI success. However, few PMI studies have employed a social network perspective or social network analysis. In this chapter, the authors review the current literature on PMI and organizational change, including the few studies that use social networks approach. The authors also identify recent developments in social networks and organizational change research that can improve our understanding of PMI processes and propose promising avenues for future research. Further, the authors identify obstacles for social network research on PMI and provide practical advice for overcoming them.

Research indicates a long historical connection between racism and nationalist ideologies. This connection has been highlighted in the resurgence of exclusionary nationalism in recent years, across many multicultural societies. This chapter discusses the notions of race, ethnicity and nation, and critically examines how racism shapes contemporary manifestations of nationalist discourse across the world. It explores the historical role of settler-colonialism, imperial expansions and the capitalist development in shaping the racial/ethnic aspect of nationalist development. Moreover, it provides an analysis of the interconnections between the racialisation of minorities, exclusionary ideologies and the consolidation of ethno-nationalist tropes. This chapter further considers the impact of demographic changes in reinforcing anti-migrant exclusionary sentiments. This is examined in connection with emerging nativist discourse, exploring how xenophobic racism has shaped and is shaped by nostalgic nationalism based on the sanitisation of the legacies of Empire and colonialism.

This study examines chronic illness, disability and social inequality within an exposure-vulnerabilities theoretical framework.

Using the National Survey of Drug Use and Health (NSDUH), a preeminent source of national behavioral health estimates of chronic medical illness, stress and disability, for selected sample years 2005–2014, we construct and analyze two foundational hypotheses underlying the exposure-vulnerabilities model: (1) greater exposure to stressors (i.e., chronic medical illness) among racial/ethnic minority populations yields higher levels of serious psychological distress, which in turn increases the likelihood of medical disability; (2) greater vulnerability among minority populations to stressors such as chronic medical illness exacerbates the impact of these conditions on mental health as well as the impact of mental health on medical disability.

Results of our analyses provided mixed support for the vulnerability (moderator) hypothesis, but not for the exposure (mediation) hypothesis. In the exposure models, while Blacks were more likely than Whites to have a long-term disability, the pathway to disability through chronic illness and serious psychological distress did not emerge. Rather, Whites were more likely than Blacks and Latinx to have a chronic illness and to have experienced severe psychological distress (both of which themselves were related to disability). In the vulnerability models, both Blacks and Latinx with chronic medical illness were more likely than Whites to experience serious psychological distress, although Whites with serious psychological distress were more likely than these groups to have a long-term disability.

Several possibilities for understanding the failure to uncover an exposure dynamic in the model turn on the potential intersectional effects of age and gender, as well as several other covariates that seem to confound the linkages in the model (e.g., issues of stigma, social support, education).

This study (1) extends the racial/ethnic disparities in exposure-vulnerability framework by including factors measuring chronic medical illness and disability which: (2) explicitly test exposure and vulnerability hypotheses in minority populations; (3) develop and test the causal linkages in the hypothesized processes, based on innovations in general structural equation models, and lastly; (4) use national population estimates of these conditions which are rarely, if ever, investigated in this kind of causal framework.