Home closure as a weapon in the Dutch war on drugs: Does judicial review function as a safety net?

Bruijn, Larissa Michelle; Vols, Michel; Brouwer, Jan

doi:10.1016/j.drugpo.2017.08.003

Cited by 6 publications

(4 citation statements)

References 41 publications

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“…In terms of data science tools, many studies provide basic descriptive statistics of manually collected and coded case law (Madsen, 2018). Some studies have shown relatively basic correlation analysis or statistical test results (Bruijn et al, 2018) whereas others have employed more complex statistical analyses, including regression analysis of case law (Dhami and Belton, 2016). Noticeably a growing number of studies have applied network analysis to legal data (Olsen and Küçüksu, 2017;Šadl and Olsen, 2017;Tarissan and Nollez-Goldbach, 2016).…”

Section: Applications Of Data Science In Lawmentioning

confidence: 99%

Data Science Applications and Implications in Legal Studies: A Perspective Through Topic Modelling

Tan¹,

Wan²,

Yan³

et al. 2022

Journal of Data Science

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Law and legal studies has been an exciting new field for data science applications whereas the technological advancement also has profound implications for legal practice. For example, the legal industry has accumulated a rich body of high quality texts, images and other digitised formats, which are ready to be further processed and analysed by data scientists. On the other hand, the increasing popularity of data science has been a genuine challenge to legal practitioners, regulators and even general public and has motivated a long-lasting debate in the academia focusing on issues such as privacy protection and algorithmic discrimination. This paper collects 1236 journal articles involving both law and data science from the platform Web of Science to understand the patterns and trends of this interdisciplinary research field in terms of English journal publications. We find a clear trend of increasing publication volume over time and a strong presence of high-impact law and political science journals. We then use the Latent Dirichlet Allocation (LDA) as a topic modelling method to classify the abstracts into four topics based on the coherence measure. The four topics identified confirm that both challenges and opportunities have been investigated in this interdisciplinary field and help offer directions for future research.

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Section: Applications Of Data Science In Lawmentioning

confidence: 99%

Data Science Applications and Implications in Legal Studies: A Perspective Through Topic Modelling

Tan¹,

Wan²,

Yan³

et al. 2022

Journal of Data Science

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show abstract

“…This particularly holds true for individuals sentenced to serve time in prison. There are plenty of examples in which an offence committed by a tenant directly leads to his or her eviction, most notably in drug-related cases (see Bruijn et al 2018). However, there are also cases in which the offender's loss of his or her home is the result of the sanction that follows the offence.…”

Section: The First Category: Offenders Who Lose Their Homementioning

confidence: 99%

Housing Ex-Offenders in the Netherlands: Balancing Neighbourhood Safety and Human Rights

Tongeren

2020

Eur J Crim Policy Res

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The Universal Declaration of Human Rights recognises stable housing as a prerequisite for an adequate standard of living. A home provides shelter and enables personal development, thus contributing to the individual's well-being. Despite this, however, many struggle to find a place to live. In the Netherlands, people with a history of criminal or antisocial behaviour ('ex-offenders') are among those whose search for housing is most problematic. They are sometimes viewed as unreliable tenants or denied access to housing out of fear for recidivism. At the same time, Dutch local authorities-responsible for maintaining public order-may (aim to) prevent an ex-offender from (re) settling in their municipality. Recent legislation in the Netherlands furthermore allows local authorities to screen and exclude people from certain urban areas based on their past behaviour. How do Dutch private and administrative actors decide between ex-offenders' housing rights on the one hand and other persons' (feelings of) safety and public order on the other? And how do the laws and policies in the Netherlands concerning the housing of exoffenders relate to the state's human rights obligations? Using doctrinal legal research methods and applying a normative, human rights framework, this paper concludes that while there are no outright violations of fundamental rights and freedoms, several approaches in the Netherlands do appear to be problematic and at odds with international obligations.

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“…For example, Hunter et al (2008, p. 79) state: 'This tradition has not been established in the United Kingdom, perhaps because we do not have a sufficient number of judges at the appropriate level who are not male and white to make such statistical analysis worthwhile'. Still, researchers have applied quantitative methods to datasets of case law from, for example, Belgium (De Jaeger 2017), the Czech Republic (Bricker 2017), France (Sulea et al 2017a), Germany (Dyevre 2015; Bricker 2017), Israel (Doron et al 2015), Latvia (Bricker 2017), the Netherlands (Vols et al 2015;Vols and Jacobs 2017;van Dijck 2018;Bruijn et al 2018), Poland (Bricker 2017), Slovenia (Bricker 2017), Spain (Garoupa et al 2012) and Sweden (Derlén and Lindholm 2018).…”

Section: Introductionmentioning

confidence: 99%

“…A large number of studies (especially outside the USA) present basic descriptive statistics of manually collected and coded case law (e.g., Bruinsma and De Blois 1997;White and Boussiakou 2009;De Jaeger 2017;Madsen 2018;Vols and Jacobs 2017). Other studies present results of relatively basic statistical tests such as correlation analysis (e.g., Doron et al 2015;Evans et al 2017;Bruijn et al 2018). A growing body of papers present results of more sophisticated statistical analyses, including regression analysis of case law (see Dhami and Belton 2016).…”

Section: Introductionmentioning

confidence: 99%

Using machine learning to predict decisions of the European Court of Human Rights

2019

Self Cite

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When courts started publishing judgements, big data analysis (i.e. large-scale statistical analysis of case law and machine learning) within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how natural language processing tools can be used to analyse texts of the court proceedings in order to automatically predict (future) judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our (relatively simple) approach highlights the potential of machine learning approaches in the legal domain. We show, however, that predicting decisions for future cases based on the cases from the past negatively impacts performance (average accuracy range from 58 to 68%). Furthermore, we demonstrate that we can achieve a relatively high classification performance (average accuracy of 65%) when predicting outcomes based only on the surnames of the judges that try the case.

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Home closure as a weapon in the Dutch war on drugs: Does judicial review function as a safety net?

Abstract: The stretched scope of the drug-related closure power together with the relatively low success rate of citizens who fight the loss of their home and a seemingly meaningless proportionality check show no sign of a safety net against the loss of one's home at the suit of a local authority.

Cited by 6 publications

References 41 publications

Data Science Applications and Implications in Legal Studies: A Perspective Through Topic Modelling

Data Science Applications and Implications in Legal Studies: A Perspective Through Topic Modelling

Housing Ex-Offenders in the Netherlands: Balancing Neighbourhood Safety and Human Rights

Using machine learning to predict decisions of the European Court of Human Rights

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