The number of cases is measured through a broad range of quantitative variables used in various studies and policy papers as key indicators of the volume of activity of national courts. Additionally, these variables, together with other data (e.g. time needed to resolve a case, number of judges, etc.) are part of a broader discourse on the efficiency of justice systems. However, such discourse can be problematic when data is not actually comparable. To raise the attention on this very relevant but poorly explored topic, this paper analyses the comparability of the caseload data by focusing on apparently simple categories like civil and commercial litigious or non-litigious cases and administrative cases. The EU Justice Scoreboard and CEPEJ data and national case definitions in France, Italy, and Romania are used to assess the most relevant justice EU datasets. The findings point towards significant differences between analysed systems that suggest extreme caution should be exercised when using such data for scholarly, legislative or policy discourses.
The challenge of comparing EU Member States judicial data
Velicogna, Marco
Co-primo
2021
Abstract
The number of cases is measured through a broad range of quantitative variables used in various studies and policy papers as key indicators of the volume of activity of national courts. Additionally, these variables, together with other data (e.g. time needed to resolve a case, number of judges, etc.) are part of a broader discourse on the efficiency of justice systems. However, such discourse can be problematic when data is not actually comparable. To raise the attention on this very relevant but poorly explored topic, this paper analyses the comparability of the caseload data by focusing on apparently simple categories like civil and commercial litigious or non-litigious cases and administrative cases. The EU Justice Scoreboard and CEPEJ data and national case definitions in France, Italy, and Romania are used to assess the most relevant justice EU datasets. The findings point towards significant differences between analysed systems that suggest extreme caution should be exercised when using such data for scholarly, legislative or policy discourses.File | Dimensione | Formato | |
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