The structure of the debate on EU integration issues. A comparative analysis of party communication in the EP 2014 elections

The results of Eurosceptic parties in the recent European parliament election provide further evidence that the “permissive consensus” on European integration blurred. This paper focuses on the structure of the debate on EU integration issues. Which EU integration issues and positions do parties put forward? Can the debate on EU integration issues be subsumed in one or several dimensions? Do they reflect national political conflicts such as the left-right and the ‘new politics’/cultural divide? Or do they form one unique or several EU-specific dimensions, e.g. national sovereignty versus integration? In order to address these questions, this paper departs from the assumption that debate on European integration is multidimensional in its nature and therefore entails a multitude of issue areas. In other words, it does not look at how socio-economic and cultural issues are related to European integration but focuses on its components, i.e. particular EU-specific policies such as EU-wide employment, environment, immigration and monetary policy. The paper departs from the cleavage theory on political di-visions and different approaches transferring them to EU politics. Two points should be noted; first, this paper does not compare the debate on European integration issues between the national level and the EU level, but whether domestic divisions are reflected at the EU level. Second, it is not concerned with the general ideo-logical profile of political parties on EU integration issues, but on EU issues that parties communicated through press releases. By doing this, the paper is concerned with the salient EU issues that parties touch upon.

Privacy Preserving Probabilistic Record Linkage (P3RL): a novel method for linking existing health-related data and maintaining participant confidentiality.

BACKGROUND Record linkage of existing individual health care data is an efficient way to answer important epidemiological research questions. Reuse of individual health-related data faces several problems: Either a unique personal identifier, like social security number, is not available or non-unique person identifiable information, like names, are privacy protected and cannot be accessed. A solution to protect privacy in probabilistic record linkages is to encrypt these sensitive information. Unfortunately, encrypted hash codes of two names differ completely if the plain names differ only by a single character. Therefore, standard encryption methods cannot be applied. To overcome these challenges, we developed the Privacy Preserving Probabilistic Record Linkage (P3RL) method. METHODS In this Privacy Preserving Probabilistic Record Linkage method we apply a three-party protocol, with two sites collecting individual data and an independent trusted linkage center as the third partner. Our method consists of three main steps: pre-processing, encryption and probabilistic record linkage. Data pre-processing and encryption are done at the sites by local personnel. To guarantee similar quality and format of variables and identical encryption procedure at each site, the linkage center generates semi-automated pre-processing and encryption templates. To retrieve information (i.e. data structure) for the creation of templates without ever accessing plain person identifiable information, we introduced a novel method of data masking. Sensitive string variables are encrypted using Bloom filters, which enables calculation of similarity coefficients. For date variables, we developed special encryption procedures to handle the most common date errors. The linkage center performs probabilistic record linkage with encrypted person identifiable information and plain non-sensitive variables. RESULTS In this paper we describe step by step how to link existing health-related data using encryption methods to preserve privacy of persons in the study. CONCLUSION Privacy Preserving Probabilistic Record linkage expands record linkage facilities in settings where a unique identifier is unavailable and/or regulations restrict access to the non-unique person identifiable information needed to link existing health-related data sets. Automated pre-processing and encryption fully protect sensitive information ensuring participant confidentiality. This method is suitable not just for epidemiological research but also for any setting with similar challenges.