Suchergebnisse

Improve your skills in visual diagnosis Speed and accuracy of diagnosis is the key to saving lives in emergency and critical care medicine. Careful visual inspection of the patient, the data (radiography, electrocardiogram), and related clues can often help providers choose the right diagnosis and ultimately the best treatment - but this knowledge comes with experience. This book provides 110 randomly presented visual diagnosis cases for self-testing, imitating real-life situations found in the emergency department setting. Written by distinguished emergency and critical care physicians, and thoroughly revised and updated throughout, this second edition includes 25% new cases and is an ideal aid for trainees preparing for Board examinations as well as an invaluable 'refresher' for qualified emergency and critical care providers.

Abstract
During political campaigns, candidates use rhetoric to advance competing visions and assessments of their country. Research reveals that the moral language used in this rhetoric can significantly influence citizens' political attitudes and behaviors; however, the moral language actually used in the rhetoric of elites during political campaigns remains understudied. Using a data set of every tweet (N=139,412) published by 39 US presidential candidates during the 2016 and 2020 primary elections, we extracted moral language and constructed network models illustrating how candidates' rhetoric is semantically connected. These network models yielded two key discoveries. First, we find that party affiliation clusters can be reconstructed solely based on the moral words used in candidates' rhetoric. Within each party, popular moral values are expressed in highly similar ways, with Democrats emphasizing careful and just treatment of individuals and Republicans emphasizing in-group loyalty and respect for social hierarchies. Second, we illustrate the ways in which outsider candidates like Donald Trump can separate themselves during primaries by using moral rhetoric that differs from their parties' common language. Our findings demonstrate the functional use of strategic moral rhetoric in a campaign context and show that unique methods of text network analysis are broadly applicable to the study of campaigns and social movements.

Abstract
The affective animosity between the political left and right has grown steadily in many countries over the past few years, posing a threat to democratic practices and public health. There is a rising concern over the role that "bad actors" or trolls may play in the polarization of online networks. In this research, we examined the processes by which trolls may sow intergroup conflict through polarized rhetoric. We developed a dictionary to assess online polarization by measuring language associated with communications that display partisan bias in their diffusion. We validated the polarized language dictionary in 4 different contexts and across multiple time periods. The polarization dictionary made out-of-set predictions, generalized to both new political contexts (#BlackLivesMatter) and a different social media platform (Reddit), and predicted partisan differences in public opinion polls about COVID-19. Then we analyzed tweets from a known Russian troll source (N = 383,510) and found that their use of polarized language has increased over time. We also compared troll tweets from 3 countries (N = 79,833) and found that they all utilize more polarized language than regular Americans (N = 1,507,300) and trolls have increased their use of polarized rhetoric over time. We also find that polarized language is associated with greater engagement, but this association only holds for politically engaged users (both trolls and regular users). This research clarifies how trolls leverage polarized language and provides an open-source, simple tool for exploration of polarized communications on social media.

Twitter and other social media platforms are believed to have altered the course of numerous historical events, from the Arab Spring to the US presidential election. Online social networks have become a ubiquitous medium for discussing moral and political ideas. Nevertheless, the field of moral psychology has yet to investigate why some moral and political ideas spread more widely than others. Using a large sample of social media communications concerning polarizing issues in public policy debates (gun control, same-sex marriage, climate change), we found that the presence of moral-emotional language in political messages substantially increases their diffusion within (and less so between) ideological group boundaries. These findings offer insights into how moral ideas spread within networks during real political discussion.

The first textbook examining all aspects of mass gathering medicine from basic medical staffing to complex risk management. Covers specific types of events and adverse events such as terrorism, sever weather, and civil disobedience. A resource for emergency medicine and EMS professionals, large event planners, venue organizers, and administrators.