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Upperdogs Versus Underdogs

Judicial Review of Administrative Drug-Related Closures in the Netherlands

Tijdschrift Recht der Werkelijkheid, Aflevering 1 2020
Trefwoorden Eviction, War on drugs, Party capability, Empirical legal research, Drug policy
Auteurs Mr. Michelle Bruijn en Dr. Michel Vols
SamenvattingAuteursinformatie

    In the Netherlands, mayors are entitled to close public and non-public premises if drug-related activities are being conducted there. Using data from the case law of Dutch lower courts, published between 2008 and 2016, this article examines the relative success of different types of litigants, and the influence of case characteristics on drug-related closure cases. We build on Galanter’s framework of ‘repeat players’ and ‘one-shotters’, to argue that a mayor is the stronger party and is therefore more likely to win in court. We categorise mayors as ‘upperdogs’, and the opposing litigants as ‘underdogs’. Moreover, we distinguish stronger mayors from weaker ones, based on the population size of their municipality. Similarly, we distinguish the stronger underdogs from the weaker ones. Businesses and organisations are classified as stronger parties, relative to individuals, who are classified as weaker parties. In line with our hypothesis, we find that mayors win in the vast majority of cases. However, contrary to our presumptions, we find that mayors have a significantly lower chance of winning a case if they litigate against weak underdogs. When controlling for particular case characteristics, such as the type of drugs and invoked defences, our findings offer evidence that case characteristics are consequential for the resolution of drug-related closure cases in the Netherlands.


Mr. Michelle Bruijn
Michelle Bruijn is promovendus en docent aan de Rijksuniversiteit Groningen. Haar onderzoek richt zich op de regulering van cannabis en de sluiting van drugspanden.

Dr. Michel Vols
Michel Vols is hoogleraar Openbare-Orderecht aan Rijksuniversiteit Groningen. Zijn onderzoek richt zich op Openbare orde en veiligheid, en het gebruik van data science (machine learning) bij het bestuderen van juridische data.
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