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Since we have seen in the previous chapter that only small part of the shareholder rights is harmonized at the European level, we explore the national regulations in this and the subsequent chapter. In this chapter, we focus in particular on procedural and information rights, including the organization of the meeting, forum rights and the disclosure of ownership information. We find that, inter alia, there are many differences in the national provisions regarding shareholder forum rights, despite article 9 of the Shareholder Rights Directive that provides shareholders with the right to ask questions. Also in the meeting’s organization there are large differences between countries, for example, regarding the use of EGMs.

In this paper, we present a critical survey of experiments on political clientelism and vote-buying. We claim that through randomization and control, field experiments represent an important tool for answering causal questions, whereas list experiments provide useful methods that improve the hard task of measuring clientelism. We show that existing experimental research gives answers to the questions of why clientelism is effective for getting votes and winning elections, who relies more on this strategy – incumbents or challengers – how much clientelism takes place, and who tend to be the favorite targets of clientelistic politicians. The relationship between clientelism and other illicit strategies for getting votes, such as electoral violence and fraud, has also been analyzed through experimental interventions. Experiments have also studied mechanisms and policies for overcoming clientelism. Finally, we show that external validity is a major source of concern that affects this burgeoning literature.

A detailed description will be provided of all the classification algorithms that have been widely used in the domain of medical science. The foundation will be laid by giving a comprehensive overview pertaining to the background and history of the classification algorithms. This will be followed by an extensive discussion regarding various techniques of classification algorithm in machine learning (ML) hence concluding with their relevant applications in data analysis in medical science and health care. To begin with, the initials of this chapter will deal with the basic fundamentals required for a profound understanding of the classification techniques in ML which will comprise of the underlying differences between Unsupervised and Supervised Learning followed by the basic terminologies of classification and its history. Further, it will include the types of classification algorithms ranging from linear classifiers like Logistic Regression, Naïve Bayes to Nearest Neighbour, Support Vector Machine, Tree-based Classifiers, and Neural Networks, and their respective mathematics. Ensemble algorithms such as Majority Voting, Boosting, Bagging, Stacking will also be discussed at great length along with their relevant applications. Furthermore, this chapter will also incorporate comprehensive elucidation regarding the areas of application of such classification algorithms in the field of biomedicine and health care and their contribution to decision-making systems and predictive analysis. To conclude, this chapter will devote highly in the field of research and development as it will provide a thorough insight to the classification algorithms and their relevant applications used in the cases of the healthcare development sector.

In 2010, the National Mediation Board (NMB) decided to base Railway Labor Act representation election outcomes on a simple majority of those voting, rather than on the majority of all eligible voters, as had been required earlier. This was widely expected to make it easier for unions to win rights to recognition in the railway and airline industries. We demonstrate that investors expected that this change would favor unions, just as they earlier had expected rule changes that made voting easier (in 2002 and 2007) to be favorable to unions, affecting stock prices of railway and airline corporations. After the 2010 change in election procedure, between 77% and 91% of all eligible employees returned ballots in NMB elections, demonstrating that a significant portion of nonvoters were not opposed to union representation, but simply were unwilling or were unable to vote. We conclude that the current voting process is fairer than the old one. However, it has not resulted in a tide of union success in these representation elections. Apparently scholars, the parties themselves, and investors all over-estimated the practical consequences of changing NMB representation election procedures.

In this chapter, we assess the ownership characteristics for the companies in our sample. For this, we do not only use ownership concentration measures such as the Herfindahl–Hirschman index but also voting power measures since ownership and voting power are not necessarily equivalent. We find that, in line with previous studies, ownership concentration and voting power of large shareholders is generally higher in continental European countries, which has important implications for corporate governance.

In this part of the book, we investigate the practical characteristics of AGMs in an extensive empirical analysis. For this, we consider the turnout rates of AGMs of seven European Member States between 2010 and 2014 in this chapter. We show that, although there are large differences in total and small shareholder turnout rates among Member States, there is an overall increasing trend in the 2010–2014 period. In contrast to what economic theory predicts, a substantial and increasing part of small shareholders actually participate in AGMs.

Cyber threats present constantly evolving and unique challenges to national security professionals at all levels of government. Public and private sector entities also face a constant stream of cyberattacks through varied methods by actors with myriad motivations. These threats are not expected to diminish in the near future. As a result, homeland security and national security professionals at all levels of government must understand the unique motivations and capabilities of malicious cyber actors in order to better protect against and respond to cyberattacks. This chapter outlines the most common cyberattacks; explains the motivations behind these attacks; and describes the federal, state, and local efforts to address these threats.

The chapter is aimed at comprehensive discovery of the basic legal tools to improve the quality of corporate governance from the standpoint of efficient revealing, preventing and shooting negative implications of internal corporate disputes. The subject of the study, in particular, is regulatory and non-regulatory enactments in this area. Within the study we employ basic approaches that allow to reveal the conditions ensuring efficient corporate governance, i.e., dialectical, historical, systemic, formal-logic, and comparative-law ones. Therewith, the main focus is on the application of system theory developments in terms of the methodological techniques to describe any system object.

Regarding the disputes between participants of the corporation, we substantiate the need of creating conditions for the highest account of opinions of all the participants in the development of collective will, as well as for restraint of major participants from potential abuses (through accumulative voting mechanism, implementing “two keys” principle, etc.). Special attention is paid to the issues of procedure and content of interest-collision transactions made by economic societies.

The authors point out definite guidelines to improve legislation in anti-conflict aspect (forms of holding general meetings of participants, exclusive and non-exclusive competence of governing bodies, the content of acts coordinating interested-party transactions, etc.).