The Voices of European Law: Legislators, Judges and Law Professors

AbstractEuropean Union legislators, CJEU judges and EU law scholars have produced streams of texts which determine both what EU law is and how it is perceived. We explore what these distinct “voices” tell us about the EU’s legal and policy priorities using a mega corpus compiling more than 200,000 legislative acts, 55,000 court rulings and opinions, and 4,000 articles from a leading EU law journal. Applying an unsupervised machine learning technique known as probabilistic topic modelling, we find that economic integration remains the focus of EU law, but that scholars tend to emphasize rights issues more and ignore certain topics, such as farming regulations, almost entirely. The relationship among these partly interdependent, partly autonomous voices, we suggest, can be conceptualized in terms of co-evolution. Legislation influences issue attention on the CJEU, which, in turn, influences what law professors choose to write about.

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The Democratic Costs of Constitutionalization— The European Case

10.1093/oso/9780198805120.003.0005 ◽

2017 ◽

Author(s):

Dieter Grimm

Keyword(s):

At Risk ◽

Economic Integration ◽

Fundamental Rights ◽

European Law ◽

European Court ◽

Political Implications ◽

The Impact ◽

The Relationship ◽

The Eu

This chapter examines the democratic costs of constitutionalization by focusing on the European case. It first considers the interdependence of democracy and constitutionalism before discussing how constitutionalization can put democracy at risk. It then explores the tension between democracy and fundamental rights, the constitutionalization of the European treaties, and the European Court of Justice’s (ECJ) two separate judgments regarding the relationship between European law and national law. It also assesses the impact of the ECJ’s jurisprudence on democracy, especially in the area of economic integration. The chapter argues that the legitimacy problem the EU faces is caused in part by over-constitutionalization and that the remedy to this problem is re-politicization of decisions with significant political implications.

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The Relationship between the EU and Member States in Constitutional Case Law: A Comparison between Western and Eastern Europe

Cambridge yearbook of European legal studies ◽

10.1017/s1528887000001300 ◽

2008 ◽

Vol 10 ◽

pp. 189-198

Author(s):

Constance Grewe

Keyword(s):

Turning Point ◽

Case Law ◽

Eastern European ◽

European Law ◽

Eu Law ◽

Constitutional Courts ◽

Member States ◽

The Relationship ◽

Constitutional Identity ◽

The Eu

It is indeed a crucial moment now that Central and Eastern European (CEE) countries have begun to join the EU. The Maastricht Treaty was itself, in several respects, a turning point in European construction; Member States then became aware of the increasing influence of EU law and started to defend their autonomy against the ‘attacks’ stemming from it. With the accession of the CEE states, the ‘Solange story: a story about national constitutional courts resisting a straightforward surrender of national legal sovereignties, and insisting on their own role as guardians of any further transfer of powers from the national to the European level’, can now enter into ‘its chapter 3’. National or constitutional identity is the main arm of resistance, and these national reactions require a rethinking of the relationship between national and European law.

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Using Machine Learning for Analyzing Sentiment Orientations Toward Eight Countries

SAGE Open ◽

10.1177/2158244020951268 ◽

2020 ◽

Vol 10 (3) ◽

pp. 215824402095126

Author(s):

Shesen Guo ◽

Ganzhou Zhang

Keyword(s):

United States ◽

Machine Learning ◽

United Kingdom ◽

Olympic Games ◽

The United States ◽

Economic Power ◽

Machine Learning Technique ◽

The United Kingdom ◽

Learning Technique ◽

The Relationship

By using machine learning technique, this article presents sentiment and concept analyses on 48,043 articles published in The Economist from 1991 through 2016. The Economist is one of the world’s most influential political and economic magazines. The article analyzes and compares the magazine’s sentiment orientations toward the Group of Seven’s ingroup member countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and its outgroup member country China. The sentiment analyses are performed on and compared between different periods of Clinton’s, Bush’s, and Obama’s administrations in the United States; Major’s, Blair’s, Brown’s, and Cameron’s cabinets in the United Kingdom; and Kohl’s, Schröder’s, and Merkel’s in Germany. The relationship between China hosting the Olympic Games or its growing economic power and the magazine’s sentiment orientations toward the country is examined. The concept analysis on the articles with extreme positivity or negativity shows that there is no difference between the ingroup and outgroup members in the topics covered in The Economist.

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Study of the Relationship between Urban Expansion and PM10 Concentration Using Multi-Temporal Spatial Datasets and the Machine Learning Technique: Case Study for Daegu, South Korea

Applied Sciences ◽

10.3390/app9061098 ◽

2019 ◽

Vol 9 (6) ◽

pp. 1098 ◽

Cited By ~ 1

Author(s):

Yun-Jae Choung ◽

Jin-Man Kim

Keyword(s):

Machine Learning ◽

Air Pollution ◽

South Korea ◽

Urban Areas ◽

Urban Expansion ◽

Landsat Images ◽

Machine Learning Technique ◽

Learning Technique ◽

Multi Temporal ◽

The Relationship

To protect the population from respiratory diseases and to prevent the damages due to air pollution, the main cause of air pollution should be identified. This research assessed the relationship between the airborne particulate concentrations (PM10) and the urban expansion in Daegu City in South Korea from 2007 to 2017 using multi-temporal spatial datasets (Landsat images, measured PM10 data) and the machine learning technique in the following steps. First, the expanded urban areas were detected from the multiple Landsat images using support vector machine (SVM), a widely used machine learning technique. Next, the annual PM10 concentrations were calculated using the long-term measured PM10 data. Finally, the degrees of increase of the expanded urban areas and of the PM10 concentrations in Daegu from 2007 to 2017 were calculated by counting the pixels representing the expanded urban areas and computing variation of the annual PM10 concentrations, respectively. The experiment results showed that there is a minimal or even no relationship at all between the urban expansion and the PM10 concentrations because the urban areas expanded by 55.27 km2 but the annual PM10 concentrations decreased by 17.37 μg/m³ in Daegu from 2007 to 2017.

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Sentenza 238/2014: EU Law and EU Values

Remedies against Immunity? - Beiträge zum ausländischen öffentlichen Recht und Völkerrecht ◽

10.1007/978-3-662-62304-6_10 ◽

2021 ◽

pp. 209-213

Author(s):

Bernardo Giorgio Mattarella

Keyword(s):

Constitutional Law ◽

Constitutional Court ◽

Forum Shopping ◽

European Law ◽

Eu Law ◽

Protection Of Human Rights ◽

The Subject ◽

Mutual Relations ◽

The Relationship ◽

The Eu

AbstractThe relationship between Judgment 238/2014 of the Italian Constitutional Court and EU law is, at first glance, apparently weak, as the subject matter of the former is not governed by the latter, nor there have been any judgments from EU courts regarding the case. However, if one considers the origin and purpose of the EU itself and the state of relations between Italy and Germany, one cannot help but examine the case from a European law perspective. Judgment 238/2014 is relevant to European law in several ways, all of which concern not only military cooperation in the EU but also the protection of human rights, the risk of forum shopping and, above all, how reliable member states are in their mutual relations. European law in turn is relevant to the present case not so much because it offers solutions but because it shows a method for settling clashes between legal systems and illustrates its inherent difficulties. Sentenza 238/2014 is an unpersuasive judgment and can be criticized from different angles: the legal one (international and constitutional law), the factual reconstruction and the judgment’s likely effects. There are, however, two possibilities of resolving the situation that Sentenza has produced: firstly the legal one, which involves the use of all possible tools to limit its effects; and secondly the diplomatic one, which implies further negotiations. European law does not provide a ground for a preference between these two options, but it suggests that none of these ways is neglected.

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What Should Investors Care About? Mutual Fund Ratings by Analysts vs. Machine Learning Technique

SSRN Electronic Journal ◽

10.2139/ssrn.3702749 ◽

2020 ◽

Author(s):

Si Cheng ◽

Ruichang Lu ◽

Xiaojun Zhang

Keyword(s):

Machine Learning ◽

Mutual Fund ◽

Machine Learning Technique ◽

Learning Technique

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The Development of a Quantitative Precipitation Forecast Correction Technique Based on Machine Learning for Hydrological Applications

Atmosphere ◽

10.3390/atmos11010111 ◽

2020 ◽

Vol 11 (1) ◽

pp. 111 ◽

Cited By ~ 2

Author(s):

Chul-Min Ko ◽

Yeong Yun Jeong ◽

Young-Mi Lee ◽

Byung-Sik Kim

Keyword(s):

Machine Learning ◽

Heavy Rainfall ◽

Extreme Rainfall ◽

Machine Learning Techniques ◽

Precipitation Forecast ◽

Machine Learning Technique ◽

Rainfall Forecast ◽

Quantitative Precipitation Forecast ◽

Correction Technique ◽

Learning Technique

This study aimed to enhance the accuracy of extreme rainfall forecast, using a machine learning technique for forecasting hydrological impact. In this study, machine learning with XGBoost technique was applied for correcting the quantitative precipitation forecast (QPF) provided by the Korea Meteorological Administration (KMA) to develop a hydrological quantitative precipitation forecast (HQPF) for flood inundation modeling. The performance of machine learning techniques for HQPF production was evaluated with a focus on two cases: one for heavy rainfall events in Seoul and the other for heavy rainfall accompanied by Typhoon Kong-rey (1825). This study calculated the well-known statistical metrics to compare the error derived from QPF-based rainfall and HQPF-based rainfall against the observational data from the four sites. For the heavy rainfall case in Seoul, the mean absolute errors (MAE) of the four sites, i.e., Nowon, Jungnang, Dobong, and Gangnam, were 18.6 mm/3 h, 19.4 mm/3 h, 48.7 mm/3 h, and 19.1 mm/3 h for QPF and 13.6 mm/3 h, 14.2 mm/3 h, 33.3 mm/3 h, and 12.0 mm/3 h for HQPF, respectively. These results clearly indicate that the machine learning technique is able to improve the forecasting performance for localized rainfall. In addition, the HQPF-based rainfall shows better performance in capturing the peak rainfall amount and spatial pattern. Therefore, it is considered that the HQPF can be helpful to improve the accuracy of intense rainfall forecast, which is subsequently beneficial for forecasting floods and their hydrological impacts.

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