Electoral Reform and Parliamentary Debates

The early twentieth century saw many democracies adopt proportional representative systems. The textbook explanation, pioneered by Rokkan, emphasize between‐party electoral competition; the rise of the Socialist vote share made Bourgeois parties prefer PR systems to maximize their seat share. While appealing, this account is not entirely compelling. Consequently, scholars are investigating within‐party explanations of support for such reforms. Particularly, Cox, Fiva, and Smith show how list PR enable party leaders to discipline members and build cohesive parties. Relying on roll‐call votes across the Norwegian 1919 electoral reform from two‐round single‐member plurality to closed‐list PR, they show that the internal party cohesion increased following the reform. We investigate how the Norwegian electoral reform changed the content of parliamentary speeches. Comparing speeches from MPs present both before and after the reform, we show how parties become more cohesive in parliamentary debates under list PR than they were under the single‐member‐district system.     

大数据时代涉众型经济犯罪案件侦查机制创新研究

大数据时代涉众型经济犯罪呈现出愈演愈烈之势,并具有受害人数多、涉及地域广、办案周期长、涉案金额大、网络敏感度高的显著特点,创新涉众型经济犯罪侦查机制意义重大,影响深远。大数据时代创新涉众型经济犯罪侦查机制是一项系统工程,需要从国家、社会、个人等层面创新预警研判机制、合成作战机制、追赃减损机制、维稳处突机制,形成协作配合、整体联动的新格局。     

Criminal history and social disadvantage as predictors of the severity of violent offending

ABSTRACT

Lethal violence is often seen as the tip of the iceberg and homicide perpetrators are seen as manifesting the most extreme number of various risk factors. This article explores whether that is the case. Using a unique data set combining data from several administrative registers with a nationally representative sample of different types of police-reported violence committed during 2010–2011 (N = 26,303 offenders) in Finland, we compare the offenders of five different types of violence (minor assault, assault, aggravated assault, attempted homicide, and completed homicide). In addition, we examine the association between the severity of violence and prior criminal history and different types of strain. The results give partial support to the hypothesis: the more serious the violence, the more crime prone and socially disadvantaged the offender. Yet, lethal offenders do not stand out alone; the division, rather, appears to be between offenders of serious (aggravated assault, attempted homicide, completed homicide) and less serious (minor assault, assault) forms of violence.     

The ICO and artificial intelligence: The role of fairness in the GDPR framework

The year 2017 has seen many EU and UK legislative initiatives and proposals to consider and address the impact of artificial intelligence on society, covering questions of liability, legal personality and other ethical and legal issues, including in the context of data processing. In March 2017, the Information Commissioner's Office (UK) updated its big data guidance to address the development of artificial intelligence and machine learning, and to provide (GDPR), which will apply from 25 May 2018.This paper situates the ICO's guidance in the context of wider legal and ethical considerations and provides a critique of the position adopted by the ICO. On the ICO's analysis, the key challenge for artificial intelligence processing personal data is in establishing that such processing is fair. This shift reflects the potential for artificial intelligence to have negative social consequences (whether intended or unintended) that are not otherwise addressed by the GDPR. The question of ‘fairness’ is an important one, to address the imbalance between big data organisations and individual data subjects, with a number of ethical and social impacts that need to be evaluated.     

Avoiding the internet of insecure industrial things

Security incidents such as targeted distributed denial of service (DDoS) attacks on power grids and hacking of factory industrial control systems (ICS) are on the increase. This paper unpacks where emerging security risks lie for the industrial internet of things, drawing on both technical and regulatory perspectives. Legal changes are being ushered by the European Union (EU) Network and Information Security (NIS) Directive 2016 and the General Data Protection Regulation 2016 (GDPR) (both to be enforced from May 2018). We use the case study of the emergent smart energy supply chain to frame, scope out and consolidate the breadth of security concerns at play, and the regulatory responses. We argue the industrial IoT brings four security concerns to the fore, namely: appreciating the shift from offline to online infrastructure; managing temporal dimensions of security; addressing the implementation gap for best practice; and engaging with infrastructural complexity. Our goal is to surface risks and foster dialogue to avoid the emergence of an Internet of Insecure Industrial Things.     

Pricing privacy – the right to know the value of your personal data

The commodification of digital identities is an emerging reality in the data-driven economy. Personal data of individuals represent monetary value in the data-driven economy and are often considered a counter performance for “free” digital services or for discounts for online products and services. Furthermore, customer data and profiling algorithms are already considered a business asset and protected through trade secrets. At the same time, individuals do not seem to be fully aware of the monetary value of their personal data and tend to underestimate their economic power within the data-driven economy and to passively succumb to the propertization of their digital identity. An effort that can increase awareness of consumers/users on their own personal information could be making them aware of the monetary value of their personal data. In other words, if individuals are shown the “price” of their personal data, they can acquire higher awareness about their power in the digital market and thus be effectively empowered for the protection of their information privacy. This paper analyzes whether consumers/users should have a right to know the value of their personal data. After analyzing how EU legislation is already developing in the direction of propertization and monetization of personal data, different models for quantifying the value of personal data are investigated. These models are discussed, not to determine the actual prices of personal data, but to show that the monetary value of personal data can be quantified, a conditio-sine-qua-non for the right to know the value of your personal data. Next, active choice models, in which users are offered the option to pay for online services, either with their personal data or with money, are discussed. It is concluded, however, that these models are incompatible with EU data protection law. Finally, practical, moral and cognitive problems of pricing privacy are discussed as an introduction to further research. We conclude that such research is needed to see to which extent these problems can be solved or mitigated. Only then, it can be determined whether the benefits of introducing a right to know the value of your personal data outweigh the problems and hurdles related to it.     

Cross border data transfer: Complexity of adequate protection and its exceptions

The majority of the fear that exists about the cloud arises due to the lack of transparency in the cloud. Fears have persisted in relation to how the data are frequently transferred in a cloud for various purposes which includes storing and processing. This is because the level of protection differs between countries and cloud users who belong to countries which provide a high level of protection will be less in favour of transfers that reduce the protection that was originally accorded to their data. Hence, to avoid client dissatisfaction, the Data Protection Directive has stated that such transfers are generally prohibited unless the country that data is being transferred to is able to provide ‘appropriate safeguards’. This article will discuss the position of the Data Protection Directive and how the new General Data Protection Regulation differs from this Directive. This involves the discussion of the similarity as well as the differences of the Directive and Regulation. In summary, it appears that the major principles of the cross border transfer are retained in the new regulation. Furthermore, the article discusses the exceptions that are provided in the standard contractual clause and the reason behind the transition from Safe Harbor to the new US-EU Privacy Shield. This article subsequently embarks on the concept of Binding Corporate Rule which was introduced by the working party and how the new regulation has viewed this internal rule in terms of assisting cross border data transfer. All the issues that will be discussed in this article are relevant in the understanding of cross border data transfer.     

Are DNA data a valid source to study the spatial behavior of unknown offenders?

Studying the spatial behaviour of unknown offenders (i.e. undetected offenders) is difficult, because police recorded crime data do not contain information about these offenders. Recently, forensic DNA data has been used to study unknown offenders. However, DNA data are only a subset of the crimes committed by unknown offenders stored in police recorded crime data. To establish the suitability of DNA data for studying the spatial offending behaviour of unknown offenders, we examine the concentration and spatial similarity of detected but unsolved crimes in police recorded crime data (N?=?181,483) and DNA data (N?=?1913) over 27 Belgian judicial districts for four crime types. We established spatial similarity for certain crime types (in some districts). This offers opportunities for DNA data to be used to study unknown offenders' spatial offending behaviour. Implications for theory and research are discussed.     

PERSONAL DATA PROTECTION: RETHINKING THE REASONS,NATURE, AND LEGAL FRAMEWORK

This paper rethinks the reasons for and the nature and means of personal data protection. The reasons for personal data protection are that it could promote the fairness and effectiveness of information flow, help individuals develop their independent personality, and equip them to deal with risks. With respect to the nature of personal data, this paper argues that such data should not be perceived from a purely individualistic point of view. Rather, there should be a contextualized understanding of the data, which considers the appropriate information flow of personal data within a particular context. Regarding the legal framework of personal data protection, this paper suggests that consumer protection law and public law are better equipped to protect personal data than tort, contract, or property law.     

Public support for state surveillance

This study examines citizens’ support for state surveillance, contingent upon factors related to policy design and the context of implementation. While most people want to live in a secure environment, we argue in this study that the support of policies to reach this goal depends on their necessity, extensiveness and reliability. Results from survey experiments in four European countries show that citizens are ready to approve the introduction of far-reaching state surveillance that includes measures of facial recognition and motion detection. Public support is further enhanced if these measures are to be targeted at potential criminals, rather than at all citizens (i.e., policy extensiveness), as well as if a safety threat is salient (i.e., policy necessity). Concerns about data security reduce support (i.e., policy reliability). While these conditions matter for the support of specific policies, they do not influence how trustworthy citizens consider government and other political authorities to be.