Empirical Legal Research
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Empirical Legal Research

A Guidance Book for Lawyers, Legislators and Regulators

Frans L. Leeuw and Hans Schmeet

Empirical Legal Research describes how to investigate the roles of legislation, regulation, legal policies and other legal arrangements at play in society. It is invaluable as a guide to legal scholars, practitioners and students on how to do empirical legal research, covering history, methods, evidence, growth of knowledge and links with normativity. This multidisciplinary approach combines insights and approaches from different social sciences, evaluation studies, Big Data analytics and empirically informed ethics. The book discusses the tensions between the normative character of law and legal issues and the descriptive and causal character of empirical legal research, and suggests ways to help handle this seeming disconnect.
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Chapter 7: Data collection methods

Frans L. Leeuw and Hans Schmeet


Thinking about the ‘units of analysis’ is an important task in empirical research; units of analysis include individuals, groups, families, officials, organizations, municipalities, courts, prisons, but also contracts, wills, guidelines, protocols and verdicts. Once the units of analysis have been selected, the next question is: who (or what) is in the unit? Are all courts within a country selected or just a sample? Is it a sample of victims under 25 or over 65, or is it the complete demographic spectrum? Are all the documents found in registers and dossiers on procurement fraud the units of analysis, or a sample from those that are less than three years old? When a population is sufficiently large, one can work with samples. If the sample is selected randomly and high-quality data collection methods are used (see below; and Chapter 8), statistical techniques to infer information about the broader population (inferential statistics) can be used. Sampling may look simple, but ‘is perhaps the messiest part of inferential empirical work’.As sampling is strongly related to the statistical analysis of data, in Chapter 8 we will discuss more in depth (statistical) aspects of sampling. Often complicated, and also dangerously messy, is the operationalization of central concepts of the study into variables that can be measured. Concepts (also known as constructs) are generalizable properties or characteristics associated with objects, events or people (Whetten, 1989; Bhattacherjee, 2012: 26–8).

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