Risk and the limits of governance: Exploring varied patterns of risk‐based governance across Europe

By H. Rothstein, O. Borraz, Michael Huber. 2013

147 citations recorded by the source corpus.

Subfields: Public Administration, Sociology and Political Science, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/6baf9a5ffe3e260294c865a4883a9f6140842058

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Public Administration

1. M. Lodge
2. D. Levi‐Faur

In Sociology and Political Science

1. D. Levi‐Faur
2. M. Lodge
3. Arjen Boin

In Strategy and Management

1. M. Lodge
2. D. Levi‐Faur
3. Fabrizio Gilardi
4. Jacint Jordana
5. Martino Maggetti

Citations in the corpus

• Data governance: Organizing data for trustworthy Artificial Intelligence (2020, unknown): “This approach is often advocated as a foundation for data governance (Rothstein, Borraz, & Huber, 2013) and an effective solution to AI-specific risks such as data or algorithmic errors, data or algorithmic bias, or even data-embedded discrimination (Janssen & Kuk, 2016).”
• Designing resilient institutions for transboundary crisis management : A time for public administration (2016, background): “A literature on risk regulation has spawned in response (Hood and Jones 1996; Rothstein et al. 2013), with some important input from public administration scholars (for example, Hood et al. 2001).”
• THE WELFARE STATE: A REGULATORY PERSPECTIVE (2014, background): “6 Additional important dimensions are the relations between the regulatory state on the one hand and the developmental state (see, Levi-Faur, 2013) and risk governance on the other(Rothstein et al., 2013; Krieger, 2013).”