The working paper constitutes a central component of the underlying project’s approach of allowing interdisciplinary comparison of the impact of different regulatory systems on individual behavior.
It is embedded in the question of the extent to which different regulatory factors and instruments, as well as different cultural settings, can influence individual data disclosure in different ways. The “Regulatory Clustering” attempts to present and compare the legal parameters as implemented by legislators in different countries, and, above all, to make them tangible for empirical (non-legal) disciplines. In order to achieve this goal, the approach is based on the idea of quantification of law.
The most important facts in brief
The quantification and quantifiability of law is something that is (with good reason) fundamentally alien to legal studies in general and comparative law in particular: a value-based construct that is rooted not only in the respective legislation, but also in the setting in which it is practiced, cannot be readily expressed as a mathematically measurable quantity. Nonetheless, the “Regulatory Clustering” measures precisely the written law in the legislation – the “law in the books” – without taking into account the practiced law – the “law in action”. Not only can the use of an objective and coherent methodology ensure a comparable quantification of the “law in the books”. It can also shift the actual questions of how the law is actually implemented in a country and how the individual perceives it, towards an interdisciplinary comparison of the “law in the books”, cultural science and behavioral economics parameters.
Key peculiarities in the analysis of the different jurisdictions:
- The fundamental idea, that the processing of personal data carries an inherent risk potential that requires regulation, runs through each of the legal systems examined. Certain regulatory concepts (such as consent or the particular importance of transparency) can be found in all the jurisdictions examined.
- The restrictive approach of the GDPR, according to which data processing is generally prohibited and, in addition, numerous objective procedural obligations are attached to processing, was found in the majority of the jurisdictions examined (Brazil, China, Germany, Ghana, Switzerland).
- Although China scores best in terms of regulatory and enforcement intensity. This sober-objective result, does directly show why comparative law should not be limited to the “law in the books”: In fact, China must be classified as having the lowest level of protection for personal data, as there are many state-oriented exceptions (e.g. social credit system) and, regardless of this, the Chinese regime is not bound by law, but it binds the law (rule of law vs. rule by law).
- Japan and the USA are committed to the free flow of data in principle, but have very different approaches to restrictions on this principle: While the USA (in particular California) focuses on the promotion and protection of individual autonomy, Japan only regulates certain processing activities that can be classified as “dangerous”, which in turn must be distinguished from the US sector-specific approach.
- The greatest de jure Brussels effect (i.e. proximity to the GDPR) was observed in Ghana and Brazil. At the same time, both countries represent the bottom end of enforcement intensity. It appears that the embedding of a foreign system in one’s own law creates obstacles in the practical enforcement and impact of this system.
Ultimately, many very different but also very similar regulatory approaches and instruments can be found in the rather confusing regulatory landscape of international data protection law. In this respect, certain similarities and differences in the effect of the respective legal systems on the individual are likely to be indicated. The refutation of this superficial indicative effect (i.e. the approximation to a “law in action”) is subsequently the task of interdisciplinary research on the perception of law. Within this interplay between indication and refutation lie the vectors of data disclosure.
RESEARCH PROJECT
