scholarly journals Modeling the EU plastic footprint: Exploring data sources and littering potential

2022 ◽  
Vol 178 ◽  
pp. 106086
Author(s):  
Andrea Martino Amadei ◽  
Esther Sanyé-Mengual ◽  
Serenella Sala
Keyword(s):  
Author(s):  
Catherine E. De Vries

This chapter introduces a benchmark theory of public opinion towards European integration. Rather than relying on generic labels like support or scepticism, the chapter suggests that public opinion towards the EU is both multidimensional and multilevel in nature. People’s attitudes towards Europe are essentially based on a comparison between the benefits of the status quo of membership and those associated with an alternative state, namely one’s country being outside the EU. This comparison is coined the ‘EU differential’. When comparing these benefits, people rely on both their evaluations of the outcomes (policy evaluations) and the system that produces them (regime evaluations). This chapter presents a fine-grained conceptualization of what it means to be an EU supporter or Eurosceptic; it also designs a careful empirical measurement strategy to capture variation, both cross-nationally and over time. The chapter cross-validates these measures against a variety of existing and newly developed data sources.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Haagsma ◽  
M Majdan ◽  
S M Pires ◽  
R Assunção

Abstract The burden of disease landscape in Europe is currently scattered with experts from diverse professional backgrounds, ranging from experts in infectious diseases, non-communicable diseases, injuries and risk factors, to experts in more comprehensive national, regional and global burden of disease studies. Currently there is little interaction between these experts and existing burden of disease efforts. The European burden of disease network (burden-eu) COST Action aims to bring together expertise across different domains and professional backgrounds. During the course of the burden-eu COST Action, several steps will be taken to facilitate interaction between existing burden of disease efforts. First, a survey has been sent around to all members of the EU burden of disease network to map burden of disease studies that have been carried out in their country. Apart from general details about the year of the study and cause of disease categories, items of the survey included data sources, methodological approach and collaborations with institutes of other countries. In the first month, the survey has been completed for over 70 studies that have been carried out in twelve countries. Second, comparison of existing burden of disease initiatives allows for the identification of the various domains for which burden of disease has been assessed, highlight methodological differences as well as similarities, and facilitate improvements and harmonization of methods and approaches. Furthermore, the data collected from the survey will be included in a continuously updated burden of disease database that lists all past and current burden of disease activities. Lastly, burden-eu will facilitate regular meetings and workshops. Each of these steps will make it possible to move beyond the currently scattered burden of disease landscape and increase interaction between professionals and burden of disease efforts.


2007 ◽  
Vol 200 ◽  
pp. 64-78 ◽  
Author(s):  
Marcel P. Timmer ◽  
Mary O'Mahony ◽  
Bart van Ark

This paper gives an overview of the construction of and preliminary results from the EU KLEMS database which contains industry estimates of output, input and productivity growth for EU countries. The paper begins with a discussion of methodology and data sources covering output and intermediates, capital and labour services. The content and scope of the database is then briefly described. This is followed by a discussion of preliminary results focusing on comparisons between the EU and US. These confirm the relatively poor productivity performance of the EU relative to the US since the mid-1990s, mostly driven by low productivity growth in market services.


Author(s):  
Zuzana Ringlerova

The European Union (EU) is a supranational political system that unites more than twenty-five European countries. European integration began to facilitate economic cooperation. Over time, it evolved into both an economic and political union. The progress in European integration accelerated in the 1980s and the 1990s. As a result, the European Union was established in 1993 and assumed more political power. The process of establishing the European Union was slowed by the results of a referendum in Denmark, which at first did not approve the treaty establishing the EU. This referendum made it clear that public support for European integration could no longer be taken for granted and that public attitudes toward the EU are crucial for the European Union’s future development. In other words, the era of permissive consensus ended and it became clear that public opinion has become a powerful force in the development of European integration. Since then, public opinion has had a clear influence on the direction of European integration in a number of ways. Examples of this influence include the rejection of the single European currency in Sweden, the failure of the Constitution for Europe, and, most notably, the United Kingdom’s decision to exit the EU. Public opinion has influenced European politics in other ways as well. For example, national political elites, acting at the European level, are constrained in their decisions by public opinion at home. The importance of understanding public opinion toward the EU has given rise to a lively research program. In their quest to understand citizens’ attitudes toward the EU, researchers first had to conceptualize the key concepts in this field, in particular the meaning of public support for the EU. Following this, scholars began to investigate why people support or oppose the European Union, which became the most widely studied topic in this field. In addition, studies have examined public support for specific European policies, determinants of voting in EU-related referendums, public support for EU membership in countries outside the EU, and the extent to which public opinion matters for policymaking in the EU. All these topics are included in this annotated bibliography. The section devoted to General Introductions and Review Articles lists review articles and textbook chapters that provide a quick overview of the topic as a whole. The next section, What Is Public Support for the EU and How Do We Explain It?, digs deeper into the concept of public support for the EU, asking how the concept is defined and what explains support for the EU. The following three sections deal with public opinion toward specific EU policies (Public Opinion toward Specific EU Policies), public support for the EU in nonmember states (Public Support for the EU in Candidate Countries and Other Nonmember States), and the question of public opinion’s influence on policymaking in the EU (Does Public Opinion Matter for Policymaking in the EU?). The second-to-last section is devoted to referendums on European matters (Referendums: Explaining the People’s Vote, Explaining Brexit). The last section (Data Sources) looks at data sources that can be used in the study of public attitudes toward the EU.


2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
F Carinci ◽  
B Meza Torres ◽  
S G Cunningham ◽  
J Mainz ◽  
O Groene ◽  
...  

Abstract Background The EU-funded Marie Curie project HEALTHPROS aims to foster a new generation of “Healthcare Performance Intelligence Professionals” through a cohesive stream of 13 doctoral projects (www.healthpros-h2020.eu). Over 48 months, researchers will investigate key levers of healthcare improvement in 7 different countries, using methods drawn from the diverse fields of biostatistics, medical informatics and health services research. Objectives To describe barriers and enablers in the conduction of two doctoral projects aimed at exploring the impact of personal risk factors and organizational arrangements on lower extremity amputations in diabetes, through the use of large-scale databases from England, Scotland, Denmark and Germany. Results The research plan included a systematic review, structured comparison of data sources, predictive modelling and software development for automated international comparisons. Barriers encountered by researchers were: knowledge and access to data sources from different countries, dealing with data protection rules and the ability to carry out international comparisons when individual records are not easily allowed to leave national boundaries. Enabling factors included: a targeted educational process for risk modelling in diabetes and a multidisciplinary support team to help doctoral students overcoming the above barriers across different sites. Further clinical insight and contextual knowledge of data systems in place at different locations were needed in addition to the statistical, epidemiological and technical skills initially foreseen by the program. Conclusions The success of studies within a general educational program on health systems performance may depend from the continued support of a multidisciplinary team helping students in their educational process as well as with the practicalities of their research. International comparisons using routine data may require prioritisation to meet the tight timelines of doctoral theses. Key messages Academic programs for international comparisons in health care may be hampered by different type of barriers including technical aspects, legal regulations and a range of contextual factors. The establishment of multidisciplinary support teams may be essential for training doctoral students aiming to conduct international comparisons using routine data.


2022 ◽  
Vol 80 (1) ◽  
Author(s):  
Brigid Unim ◽  
Eugenio Mattei ◽  
Flavia Carle ◽  
Hanna Tolonen ◽  
Enrique Bernal-Delgado ◽  
...  

Abstract Background Health-related data are collected from a variety of sources for different purposes, including secondary use for population health monitoring (HM) and health system performance assessment (HSPA). Most of these data sources are not included in databases of international organizations (e.g., WHO, OECD, Eurostat), limiting their use for research activities and policy making. This study aims at identifying and describing collection methods, quality assessment procedures, availability and accessibility of health data across EU Member States (MS) for HM and HSPA. Methods A structured questionnaire was developed and administered through an online platform to partners of the InfAct consortium form EU MS to investigate data collections applied in HM and HSPA projects, as well as their methods and procedures. A descriptive analysis of the questionnaire results was performed. Results Information on 91 projects from 18 EU MS was collected. In these projects, data were mainly collected through administrative sources, population health interview or health examination surveys and from electronic medical records. Tools and methods used for data collection were mostly mandatory reports, self-administered questionnaires, or record linkage of various data sources. One-third of the projects shared data with EU research networks and less than one-third performed quality assessment of their data collection procedures using international standardized criteria. Macrodata were accessible via open access and reusable in 22 projects. Microdata were accessible upon specific request and reusable in 15 projects based on data usage licenses. Metadata was available for the majority of the projects, but followed reporting standards only in 29 projects. Overall, compliance to FAIR Data principles (Findable, Accessible, Interoperable, and Reusable) was not optimal across the EU projects. Conclusions Data collection and exchange procedures differ across EU MS and research data are not always available, accessible, comparable or reusable for further research and evidence-based policy making. There is a need for an EU-level health information infrastructure and governance to promote and facilitate sharing and dissemination of standardized and comparable health data, following FAIR Data principles, across the EU.


2013 ◽  
Author(s):  
Rinus van Schendelen
Keyword(s):  

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