Self-regulation in Science
Self-regulation is the process whereby an organization is either asked or volunteers to monitor its own adherence to legal, ethical, or safety standards, rather than having an independent external agency such as a government entity monitor and enforce those standards.
The adoption of regulatory approaches developed by scientists themselves has become an increasingly established way of governing scientific research. In this context, self-regulation generally refers to the development of specific self-imposed behavioral norms, primarily within the framework of professional standard-setting. While it originally meant the adoption of technical standards, the normative dimension of rules based on self-regulation in scientific research contexts regularly goes beyond a solely technical dimension. In this context, therefore, self-regulation can be described as self-standardizing in the sense of self-commitment and self-control.[1]
Self-regulatory measure can be helpful in research contexts. Firstly, they can have important indirect legal relevance because they create legal certainty and a waiver of liability in civil, labor and even criminal law.[2]
Secondly, self-regulatory approaches in scientific research can help ensure the necessary specificity of rules for this regulatory context, such as legal principles which can be specialized to identify specific decision-making methods and action corridors. The participation of norm addressees in the development of rules helps take account of their specific expertise and increase the effectiveness and efficiency of said rules.[3]
Thirdly, self-regulation can ensure the timely pursuit of specific technological and scientific developments, as the preparation of such rules usually takes little time compared to legislative measures.[4]
However, such self-regulatory (private) rule-making must remain in line with the respective legal system and any interpretation of established rules must be compliant with that system. Additionally, self-regulatory solutions can only win trust and develop any normative effect if they are broadly supported at the professional and societal level. At the same time, the legitimacy and steering effect of such rules can best be ensured through the specific accumulation of expertise during the course of their development.[5]
See also[edit]
References[edit]
- ↑ Molnar-Gabor. Maßstäbe der Selbstregulierung in der Krebsforschung, in: Taeger et al. (eds.) Smart World – Smart Law? 901 et seq., 908 et seq.
- ↑ Famenka et al. Understanding the Complexity of Regulation in an Evolving Health Technology Landscape, in: Dreyer et al. Genetic transparency? Brill 2016, 193 et seq., 225 et seq.
- ↑ Famenka et al. Understanding the Complexity of Regulation in an Evolving Health Technology Landscape, in: Dreyer et al. Genetic transparency? Brill 2016, 229 et seq.
- ↑ Molnar-Gabor. Maßstäbe der Selbstregulierung in der Krebsforschung, in: Taeger et al. (eds.) Smart World – Smart Law? 912 et seq.
- ↑ Molnar-Gabor. Maßstäbe der Selbstregulierung in der Krebsforschung, in: Taeger et al. (eds.) Smart World – Smart Law? 908
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