no / Since 1989 Romania has gone from communist isolation under the megalomaniac Nicolae Ceauescu to being a key player in America's war against terrorism. Because of this strategic location it has become a front-line state for nervous Western governments keen to secure oil routes from the Middle East. It joined NATO in 2004 and is due to enter the European Union in 2007-08 despite its economy being unprepared to meet the competition challenges from established members. Tom Gallagher analyses how the country is seeking to recover from a disastrous period in its history while many of the key legacies of dictatorship remain. Having lynched the discredited Ceauescu in 1989, former acolytes have spent the past fifteen years trying to retain a monopoly of control behind the facade of a Western-style democracy. They combined their political ambitions with acquiring the control of vast amounts of private property denied to them by Ceauescu. Political institutions were given a facelift, as in the case of the intelligence services which became a crucial power-base for the ruling Social Democratic Party (PSD). The state continued to be used to serve narrow private interests. Replacing the communist dynasty of the Ceauescus, there is now an oligarchy drawn from the PSD and its satellites in the bureaucracy, major industries, and the intelligence world which grew wealthy through insider privatisation and the looting of the country's banks. Romania is now at a crucial turning-point. In 2004 the mobilisation of civil society contributed to the narrow victory of Traian B sescu in presidential elections. It is unclear whether he can win control over the key levers of state necessary to stem the corruption and abuse of power which have blighted Romania's hopes of breaking free from its communist-era legacy. The PSD is now led by Mircea Geoana, the son of a general in Ceauescu's Securitate. He has recruited a string of Western politicians to block pressure for meaningful change from Brussels and to ensure that accession to the EU occurs without serious reform.

This thesis argues that neopatrimonialism is vital to understanding the power structure of the secessionist Transnistrian Moldovan Republic (TMR), and that neopatrimonial structures have been manipulated by Soviet-era elites to sustain the unrecognized separatist state's independence. The thesis also argues that neopatrimonialism is not a stable structure and its effectiveness in retaining support for the regime has changed over time. The paper provides an empirical analysis of the TMR in order to answer two questions: "To what extent does neopatrimonialism explain the regime endurance of the Transnistrian Moldovan Republic?" and "What does the case of the Transnistrian Moldovan Republic reveal about neopatrimonialism and regime endurance over time?" The analysis examines the TMR regime's use of Soviet-era industrial and bureaucratic structures, media, party networks, and worker committees to assert and maintain control, distribute patronage, maintain support for secession, and co-opt important interest groups. The paper concludes that although neopatrimonialism is only one of several elements that support the TMR regime's endurance, the analysis of neopatrimonial systems in states with significant neopatrimonialism provides a framework for examining disparate but interwoven elements of a state's political economy. / Master of Public and International Affairs

The presence of noise and corruption in real-world data can be inevitably caused by accidental outliers, transmission loss, or even adversarial data attacks. Unlike traditional random noise usually assume a specific distribution with low corruption ratio, the data collected from crowdsourcing or labeled by weak annotators can contain adversarial data corruption. More challenge, the adversarial data corruption can be arbitrary, unbounded and do not follow any specific distribution. In addition, in the era of data explosion, the fast-growing amount of data makes the robust models more difficult to handle large-scale data sets. This thesis focuses on the development of methods for scalable robust models under the adversarial data corruption assumptions. Four methods are proposed, including robust regression via heuristic hard-thresholding, online and distributed robust regression with adversarial noises, self-paced robust learning for leveraging clean labels in noisy data, and robust regression via online feature selection with adversarial noises. Moreover, I extended the self-paced robust learning method to its distributed version for the scalability of the proposed algorithm, named distributed self-paced learning in alternating direction method of multiplier. Last, a robust multi-factor personality prediction model is proposed to hand the correlated data noises. For the first method, existing solutions for robust regression lack rigorous recovery guarantee of regression coefficients under the adversarial data corruption with no prior knowledge of corruption ratio. The proposed contributions of our work include: (1) Propose efficient algorithms to address the robust least-square regression problem; (2) Design effective approaches to estimate the corruption ratio; (3) Provide a rigorous robustness guarantee for regression coefficient recovery; and (4) Conduct extensive experiments for performance evaluation. For the second method, existing robust learning methods typically focus on modeling the entire dataset at once; however, they may meet the bottleneck of memory and computation as more and more datasets are becoming too large to be handled integrally. The proposed contributions of our work for this task include: (1) Formulate a framework for the scalable robust least-squares regression problem; (2) Propose online and distributed algorithms to handle the adversarial corruption; (3) Provide a rigorous robustness guarantee for regression coefficient recovery; and (4) Conduct extensive experiments for performance evaluations. For the third method, leveraging the prior knowledge of clean labels in noisy data is actually a crucial issue in practice, but existing robust learning methods typically focus more on eliminating noisy data. However, the data collected by ``weak annotator" or crowd-sourcing can be too noisy for existing robust methods to train an accurate model. Moreover, existing work that utilize additional clean labels are usually designed for some specific problems such as image classification. These methods typically utilize clean labels in large-scale noisy data based on their additional domain knowledge; however, these approaches are difficult to handle extremely noisy data and relied on their domain knowledge heavily, which makes them difficult be used in more general problems. The proposed contributions of our work for this task include: (1) Formulating a framework to leverage the clean labels in noisy data; (2) Proposing a self-paced robust learning algorithm to train models under the supervision of clean labels; (3) Providing a theoretical analysis for the convergence of the proposed algorithm; and (4) Conducting extensive experiments for performance evaluations. For the fourth method, the presence of data corruption in user-generated streaming data, such as social media, motivates a new fundamental problem that learns reliable regression coefficient when features are not accessible entirely at one time. Until now, several important challenges still cannot be handled concurrently: 1) corrupted data estimation when only partial features are accessible; 2) online feature selection when data contains adversarial corruption; and 3) scaling to a massive dataset. This paper proposes a novel RObust regression algorithm via Online Feature Selection (textit{RoOFS}) that concurrently addresses all the above challenges. Specifically, the algorithm iteratively updates the regression coefficients and the uncorrupted set via a robust online feature substitution method. We also prove that our algorithm has a restricted error bound compared to the optimal solution. Extensive empirical experiments in both synthetic and real-world data sets demonstrated that the effectiveness of our new method is superior to that of existing methods in the recovery of both feature selection and regression coefficients, with very competitive efficiency. For the fifth method, existing self-paced learning approaches typically focus on modeling the entire dataset at once; however, this may introduce a bottleneck in terms of memory and computation, as today's fast-growing datasets are becoming too large to be handled integrally. The proposed contributions of our work for this task include: (1) Reformulate the self-paced problem into a distributed setting.; (2) A distributed self-paced learning algorithm based on consensus ADMM is proposed to solve the textit{SPL} problem in a distributed setting; (3) A theoretical analysis is provided for the convergence of our proposed textit{DSPL} algorithm; and (4) Extensive experiments have been conducted utilizing both synthetic and real-world data based on a robust regression task. For the last method, personality prediction in multiple factors, such as openness and agreeableness, is growing in interest especially in the context of social media, which contains massive online posts or likes that can potentially reveal an individual's personality. However, the data collected from social media inevitably contains massive amounts of noise and corruption. To address it, traditional robust methods still suffer from several important challenges, including 1) existence of correlated corruption among multiple factors, 2) difficulty in estimating the corruption ratio in multi-factor data, and 3) scalability to massive datasets. This paper proposes a novel robust multi-factor personality prediction model that concurrently addresses all the above challenges by developing a distributed robust regression algorithm. Specifically, the algorithm optimizes regression coefficients of each factor in parallel with a heuristically estimated corruption ratio and then consolidates the uncorrupted set from multiple factors in two strategies: global consensus and majority voting. We also prove that our algorithm benefits from strong guarantees in terms of convergence rates and coefficient recovery, which can be utilized as a generic framework for the multi-factor robust regression problem with correlated corruption property. Extensive experiment on synthetic and real dataset demonstrates that our algorithm is superior to those of existing methods in both effectiveness and efficiency. / Doctor of Philosophy / Social media has experienced a rapid growth during the past decade. Millions of users of sites such as Twitter have been generating and sharing a wide variety of content including texts, images, and other metadata. In addition, social media can be treated as a social sensor that reflects different aspects of our society. Event analytics in social media have enormous significance for applications like disease surveillance, business intelligence, and disaster management. Social media data possesses a number of important characteristics including dynamics, heterogeneity, noisiness, timeliness, big volume, and network properties. These characteristics cause various new challenges and hence invoke many interesting research topics, which will be addressed here. This dissertation focuses on the development of five novel methods for social media-based spatiotemporal event detection and forecasting. The first of these is a novel unsupervised approach for detecting the dynamic keywords of spatial events in targeted domains. This method has been deployed in a practical project for monitoring civil unrest events in several Latin American regions. The second builds on this by discovering the underlying development progress of events, jointly considering the structural contexts and spatiotemporal burstiness. The third seeks to forecast future events using social media data. The basic idea here is to search for subtle patterns in specific cities as indicators of ongoing or future events, where each pattern is defined as a burst of context features (keywords) that are relevant to a specific event. For instance, an initial expression of discontent gas price increases could actually be a potential precursor to a more general protest about government policies. Beyond social media data, in the fourth method proposed here, multiple data sources are leveraged to reflect different aspects of the society for event forecasting. This addresses several important problems, including the common phenomena that different sources may come from different geographical levels and have different available time periods. The fifth study is a novel flu forecasting method based on epidemics modeling and social media mining. A new framework is proposed to integrate prior knowledge of disease propagation mechanisms and real-time information from social media.

Yes / Exposure to political corruption and political uncertainty separately demands opposing risk management responses: to reduce cash to minimize expropriation and to increase cash to hedge policy risk. We study how local political corruption and political uncertainty interact in their impact on corporate cash holdings within the United States. We find robust evidence that firms located in states with higher corruption scores react to increases in local political uncertainty by increasing cash holdings more than those in less corrupt settings. This behavior suggests that firms in more corrupt settings find it expedient to raise cash to facilitate influence of officials in the face of local political risk. We find further support for this conclusion by showing that politically engaged firms respond to our measure of political risk by increasing cash and increasing spending on campaign contributions. Our findings point to a potential channel through which different jurisdictions experience the entrenchment and persistence of corruption.

Ce mémoire cherche à évaluer la culpabilité de Socrate face à l’échec et à la corruption d’Alcibiade, telle que la question se pose dans le Banquet de Platon. Il comprend quatre chapitres. Le premier démontre que le cadre dramatique lui-même fait occuper une place centrale à la vie et au déclin d’Alcibiade et au problème de la responsabilité de Socrate face aux accusations de corruption de la jeunesse qui ont pesé sur lui. Le deuxième chapitre interprète le discours d’Alcibiade comme une tentative de disculpation qui repose sur une critique acerbe du comportement de Socrate. Il se serait détourné de Socrate et de ses enseignements en raison de son ironie, de son arrogance et de son indifférence – de son hybris. Le troisième chapitre étudie le discours de Socrate sur l’accession à la beauté intelligible. Il expose la nature particulière de son éros, qui repose sur l’ironie et l’inversion des rôles comme moyens d’exhorter à la philosophie. Le quatrième chapitre pose la question de l’efficacité de ce type de pédagogie et de la responsabilité du philosophe vis-à-vis de ses disciples. L’étude conclut que l’amour et l’ironie de Socrate sont essentiellement des moyens d’inviter l’autre à se remettre lui-même en question et à prendre soin de son âme. Socrate n’est donc pas coupable d’avoir corrompu Alcibiade. La faute est entièrement celle du jeune homme. Il s’est montré incapable, par égocentrisme et fierté excessive, de réagir correctement à l’énigme posée par le comportement érotique de Socrate. / This essay on Plato’s Symposium assesses to what extent Socrates could be held guilty for Alcibiades’ failure and corruption. The first of the four chapters shows that Alcibiades’ life and decline and the accusation against Socrates of youth corruption are central to the dramatic structure. The second chapter interprets Alcibiades’ speech as a sharp criticism of Socrates’ behaviour meant to exculpate himself. Alcibiades justifies his walking away from Socrates and his teachings on the basis of the philosopher’s irony, arrogance and indifference – his hybris. The third chapter looks at Socrates’ speech, which sets out the path to the highest form of Beauty. It explores the particular nature of his eros, which relies especially on irony and role inversion to induce philosophical thinking. The fourth chapter asks how effective this kind of pedagogy is, and what is the responsibility of the philosopher to his students. It is concluded that Socratic love and irony are essentially to be conceived of as means of inciting followers to put themselves into question and take greater care of their souls. Socrates is thus not guilty of corrupting the young man. The fault is entirely Alcibiades’. His pride and selfishness are what prevented him from meeting the challenge that Socrates’ erotic behavior put before him.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

Title: Protection against corruption and bribery and their prevention Abstract This thesis deals with corruption and ways of its prevention. Initial chapter describes phenomenon of corruption in society, defines it and its Subchapter contains kinds of corruption. I try to explain the cause of origin of the corruption and its development phases in Chapter Two. Following Chapter Three is focused on measurement of corruption level and on existing corruption measurement methods also. This chapter concerns with description of Corruption Perception Index (CPI) published by Transparency International. The most important part of this diploma thesis is Chapter Four. This chapter is trying to find the suitable preventive measures that could reduce occurrences of corruption. Because this topic is very voluminous, Subchapter One is focused on preventive anti-corruption measures in subsequent three areas: legislative process (I describe much discussed topic of lobbing today in this part), conflict of interests and corruption in public administration. I try to describe particular measures that can reduce creating of corruption opportunities. Subchapter Two contains legislation of the corruption with put emphasis on anti-corruption tools of criminal law. It describes bribery crimes especially. Chapter Five explores ways...

ABSTRACT This thesis evaluates the effectiveness of public sector anti-corruption reform efforts in democratic South Africa. These reforms are contextualized within the international theory, literature and policy debate that has emerged over the past decade on the control of corruption within the context of democratic governance. To evaluate the effectiveness of anti-corruption reforms the thesis first covers a number of broad themes including: conceptions, causes and consequences of corruption; main theoretical approaches underpinning anti-corruption reforms; and methodologies to evaluate the effectiveness and seriousness of anti-corruption efforts. Specifically focusing on South Africa, the thesis looks at the nature and extent of corruption both pre and post 1994; recent legislative, institutional, and policy interventions to control public sector corruption; and, as an illustrative case study of grand corruption, an in-depth analysis of the government’s handling of allegations of corruption in the Strategic Defense Procurement Package or “arms deal.” The findings of the thesis are mixed: I argue that democracy is a necessary albeit insufficient condition for effectively fighting corruption. Although South Africa has an impressive array of institutions, laws and policies to counter public sector corruption, the most important ingredient for successful reforms, namely an indication of sustained political will, is not yet fully in evidence. The government’s mishandling of allegations of corruption in the arms deal is a case in point, suggesting chronic weaknesses on the part of institutions such as parliament to safeguard the public interest. Lack of regulation in the funding of political parties remains the “Achilles heel” of anti-corruption reform efforts. So far as concerns further theoretical framing of corruption studies I conclude that a focus on social empowerment (Johnston) in the context of democratic consolidation, including an active civil society and vigilant media, is crucial for the effective fight against corruption in new democracies such as South Africa.

This doctoral thesis deals with the selected criminal aspects of corruption pointing out the possibilities to sanction its most severe forms by means of the Czech criminal law. From the substantive point of view, the core of the thesis is the analysis of the bribery crimes and the thorough analysis of their selected elements, which can bring about interpretative and related application problems. It also refers to the issue of corruption in the private sector and the manner in which the Czech national legislation of corruption crimes copes with a requirement for its sanctioning, which follows from international commitments. In terms of procedural aspects, the thesis focuses on certain particulars of detection, investigation and evidence procedure relating to corruption criminality. Corruption criminality is regarded as latent criminality and in its most serious forms it is also connected to organized crime, which consequently requires application of specific means and methods in criminal procedure. However, in the course of their realization they are predominantly connected with an interference with individual's fundamental rights, so, as a reaction to that, a consistent legislation of conditions for their realization ought to be adopted. The thesis points out the shortcomings or problematic...

Cette thèse se propose d’analyser toutes les questions liées au financement descampagnes électorales en vue des élections présidentielles. En effet, l’éclosion desaffaires de corruption politique, ayant révélé l’influence de l’argent dans la viepolitique, le financement des campagnes électorales a fait l’objet de débats dansplusieurs démocraties. Une comparaison entre la France et le Brésil, deuxdémocraties ou les systèmes électoraux différent, tente de montrer que le pouvoir del’argent peut influencer les élections, spécialement celles du président de laRépublique. Cette recherche aborde donc des questions relatives à laréglementation et au contrôle du financement des campagnes électorales à la Hautefonction publique. Y sont décrits de manière exhaustive avec pour modèlecomparative, les points positifs ainsi que les faiblesses des deux systèmes face à unmême ‘’ennemi’’ : l’influence de l’argent dans la vie politique. / This thesis intends to analyse all matters regarding financing election campaigns inpresidential elections. Actually, after political corruption outbreaks, revealing theinfluence money has on politics, financing of the election campaigns turned out to bethe object of discussion in many democracies. A comparison between France andBrazil, two democracies with two different electoral systems, intends to show how thepower of money can influence election, mainly in presidential campaigns. Thisresearch address issues relating to regulation and control of election campaignsfinancials of the highest public role. They are exhaustively described, having ascomparative models France and Brazil, strong points as well as weak points of bothsystems facing the same enemy: the influence of money in the political life.