177
we investigate how these two aspects are dealt with in the fi ve cases of environmental
governance in the Baltic Sea.
Emphasising the importance of organisational structures and procedural
interactions of the science-policy interface highlights if and how the challenges
connected with assessment -management interactions differ between the fi ve cases
analysed in this study (as seen, e.g., when comparing fi sheries and eutrophication –
cf. Karlsson et al. 2016 ; Linke et al. 2014 ; Sellke et al. 2016 ). Stirling ( 2010 : 1029)
has argued with regard to the neglect of such relevant differences that an ‘overly
narrow focus on risk is an inadequate response to incomplete knowledge’, because
it makes the (necessarily simplifi ed) science-based advice vulnerable to social interests,
political manipulation and pressures from lobby groups. Stirling therefore suggests
an ‘opening up’ of linear, scientifi c conceptions of the science-policy interface for
more plural and situated understandings (Stirling 2008 : 262). He also suggests it is
necessary to take a more careful account of the nature of the knowledge at hand by
saying that ‘when the intrinsically plural, conditional nature of knowledge is
recognised, I believe that science advice can become more rigorous, robust and
democratically accountable’ (Stirling 2010 : 1029). In order to better adapt sciencepolicy interactions to these insights, he has developed an ‘uncertainty matrix’ that
differentiates between four different idealised states of incomplete knowledge
(Fig. 8.2 ).
The formal state of risk (Fig. 8.2 ) is characterised by a comparatively high level
of confi dence in both the knowledge about possible outcomes as well as about their
respective probabilities. It can thus be handled by traditional linear risk assessment -
management procedures based on a straightforwardly applied scientifi c approach
(as in Fig. 8.1 ). However, this is not the case in the three other cases of the matrix,
namely, uncertainty , ambiguity and ignorance , which according to Stirling differ
from the traditional risk categorisation.
Under the condition of scientifi c uncertainty , it is still feasible to characterise
possible outcomes but the available information input (data) is too incomplete to
assign specifi c probabilities (e.g. as often is argued for the enormous number of
chemical pollutants in the environment). For such (uncertain) environmental issues,
as Stirling ( 2007 : 310) notes, ‘the scientifi cally rigorous approach is therefore to
acknowledge various possible interpretations’.
The condition of ambiguity is, on the other hand, not primarily characterised by
problematic knowledge about probabilities (data input) but about the possible outcomes and contested interpretations and framings of the environmental issue. The
management of various marine resources, such as commercial fi sh stocks, has been
argued to belong to this type of an environmental issue (cf. Linke et al. 2014 ). For
such cases, disagreements among disciplines and specialists may arise as a consequence of different integration of ecological, agronomic, safety or socio-economic
criteria of harm. Therefore, the application of a traditional natural science-based
assessment alone is neither rigorous nor rational (Stirling 2007 ) and needs to be
complemented with social science-based ‘concern appraisals’ (Renn 2008 ).
Finally, the condition of ignorance is one where neither the knowledge about
probabilities nor about outcomes can be made fully clear (as argued to be the case
8 Science-Policy Interfaces in Baltic Sea Environmental Governance: Towards…
we investigate how these two aspects are dealt with in the fi ve cases of environmental
governance in the Baltic Sea.
Emphasising the importance of organisational structures and procedural
interactions of the science-policy interface highlights if and how the challenges
connected with assessment -management interactions differ between the fi ve cases
analysed in this study (as seen, e.g., when comparing fi sheries and eutrophication –
cf. Karlsson et al. 2016 ; Linke et al. 2014 ; Sellke et al. 2016 ). Stirling ( 2010 : 1029)
has argued with regard to the neglect of such relevant differences that an ‘overly
narrow focus on risk is an inadequate response to incomplete knowledge’, because
it makes the (necessarily simplifi ed) science-based advice vulnerable to social interests,
political manipulation and pressures from lobby groups. Stirling therefore suggests
an ‘opening up’ of linear, scientifi c conceptions of the science-policy interface for
more plural and situated understandings (Stirling 2008 : 262). He also suggests it is
necessary to take a more careful account of the nature of the knowledge at hand by
saying that ‘when the intrinsically plural, conditional nature of knowledge is
recognised, I believe that science advice can become more rigorous, robust and
democratically accountable’ (Stirling 2010 : 1029). In order to better adapt sciencepolicy interactions to these insights, he has developed an ‘uncertainty matrix’ that
differentiates between four different idealised states of incomplete knowledge
(Fig. 8.2 ).
The formal state of risk (Fig. 8.2 ) is characterised by a comparatively high level
of confi dence in both the knowledge about possible outcomes as well as about their
respective probabilities. It can thus be handled by traditional linear risk assessment -
management procedures based on a straightforwardly applied scientifi c approach
(as in Fig. 8.1 ). However, this is not the case in the three other cases of the matrix,
namely, uncertainty , ambiguity and ignorance , which according to Stirling differ
from the traditional risk categorisation.
Under the condition of scientifi c uncertainty , it is still feasible to characterise
possible outcomes but the available information input (data) is too incomplete to
assign specifi c probabilities (e.g. as often is argued for the enormous number of
chemical pollutants in the environment). For such (uncertain) environmental issues,
as Stirling ( 2007 : 310) notes, ‘the scientifi cally rigorous approach is therefore to
acknowledge various possible interpretations’.
The condition of ambiguity is, on the other hand, not primarily characterised by
problematic knowledge about probabilities (data input) but about the possible outcomes and contested interpretations and framings of the environmental issue. The
management of various marine resources, such as commercial fi sh stocks, has been
argued to belong to this type of an environmental issue (cf. Linke et al. 2014 ). For
such cases, disagreements among disciplines and specialists may arise as a consequence of different integration of ecological, agronomic, safety or socio-economic
criteria of harm. Therefore, the application of a traditional natural science-based
assessment alone is neither rigorous nor rational (Stirling 2007 ) and needs to be
complemented with social science-based ‘concern appraisals’ (Renn 2008 ).
Finally, the condition of ignorance is one where neither the knowledge about
probabilities nor about outcomes can be made fully clear (as argued to be the case
8 Science-Policy Interfaces in Baltic Sea Environmental Governance: Towards…