What to expect from Science? How controversies and uncertainties affects the legitimacy of knowledge-based management in the Norwegian aquaculture context

Speaker: Maiken Bjørkan # Nordland Research Institute

27th Nov 2017

15:30 - 17:00

Chrystal Macmillan Building, 6th Floor Staff Room

It is a common perception that ‘the larger the knowledge base, the easier to make decisions’. In contexts where uncertainties can to be reduced through the incorporation of more knowledge this can be a possible scenario. However, the question of what the best and most relevant available knowledge is, can become the subject of a political discussion in itself, and actually create rather than resolve, conflicts in political affairs with strong conflicts of interest.

In Norway, the current and rather heated debate between the key advisory bodies (IMR and NINA) and The Norwegian Seafood Association (industry organization) is an example of how actors can question and contest the science that underpins advice. With regards to sea lice and its related regulations, the industry organization “the Norwegian Seafood Association” questions both the assumptions that advice is based on and the quality of the knowledge itself. The advisory bodies are now reacting to some of the criticism as they find it to be personal attacks rather than professional and relevant, threatening with legal action.

Here, I will discuss how the authority and legitimacy of scientific advice is challenged in relation to some of the ethical standards in place (in Norway) to guide scientists and ensure sound science, namely the precautionary approach, sustainable development, quality in research and stakeholders’ participation. Leaning on the postnormal litterature to categorize and discuss uncertainty, I use the example of the new growth model, referred to as the “traffic light system”. It is a case that exemplifies how the controversies related to uncertainty of the issue easily spills over to the science that is mobilized to manage it, and that we need to discuss what we can expect from science in knowledge production for complex matters where uncertainty may never be controlled.