When analysing the legitimacy of the welfare state, perceptions of the overuse and underuse of welfare are of great importance. Previous literature suggests that many people perceive overuse (misuse or fraud), and there is evidence that people also perceive underuse (non-take-up) of welfare benefits. Perceptions of overuse have therefore been called ‘the Achilles’ heel of welfare state legitimacy'. We analyse data from the European Social Survey for 25 countries and investigate the occurrence and the individual and contextual determinants of overuse and underuse perceptions. We find that both overuse and underuse perceptions are prevalent in all European countries. However, whereas overuse perceptions are more related to ideology, collective images of welfare recipients and selective welfare regimes, underuse perceptions are more shaped by self-interest and the levels of unemployment and social spending in a country. Instead of one Achilles' heel, welfare state legitimacy seems to have two weak spots.Key words: Benefit abuse, European Social Survey, non-take-up, welfare attitudes, welfare states
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The Internet and computers increasingly determine our daily lives. This goes for almost everyone in the Netherlands. Still, it is mostly teenagers who are well informed on how to use all the possibilities of new technologies. They are building a digital world of their own that parents usually know very little about. This booklet intends to inform teachers, parents and other interested parties on what teenagers are actually doing online and how important it is to keep abreast of the new developments that the Internet and computers bring into their world. On the basis of research into these issues in the Netherlands and abroad we attempt to indicate what the digital world of teenagers looks like and how it differs from that of grown-ups. What do they do, exactly, and why? We also look into teenagers’ ICT behaviour and into dangers and abuse of the Internet. Moreover we provide tips for parents and teachers on how to handle certain phenomena. This book does not pretend to provide an exhaustive overview of the digital world of teenagers. It is focused on some important characteristics and parts of that world. It reports on research of the INHOLLAND Centre for eLearning into various aspects of ICT behaviour among teenagers. The research was undertaken in the spring of 2006, focusing mainly on texting, networking, gaming, dangers and abuse on the Internet and the digital relation between school and the home. Ultimately we are especially concerned with the question of what teenagers really learn in their digital world, and how education can profit. This book also addresses that issue.
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"Background: Victimization is highly prevalent in individuals with mild intellectual disability (MID) or borderline intellectual functioning (BIF) and is an important risk factor for mental health problems and violent behavior. Not much is known, however, about victimization history in women with MID-BIF admitted to forensic mental health care. Aims: The aim of this multicenter study is to gain insight into victimization histories and mental health problems of female forensic psychiatric patients with MID-BIF. Methods: File data were analyzed of 126 women with MID-BIF who have been admitted to one of five Dutch forensic psychiatric hospitals between 1990 and 2014 and compared to data of 76 female patients with average or above intellectual functioning and to a matched sample of 31 male patients with MID-BIF. Results: All forensic paients had high rates of victimization, but women with MID-BIF showed an even higher prevalence of victimization during both childhood and adulthood and more complex psychopathology compared to female patients without MID-BIF. Compared to male forensic patients with MID-BIF, women with MID-BIF were more often victim of sexual abuse during childhood. During adulthood, the victimization rate in these women was more than three times higher than in men. Conclusions: Victimization is a salient factor in female forensic patients with MID-BIF and more gender-responsive trauma-focused treatment is needed."
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Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
