Environmental Engineering Reference
In-Depth Information
Knowledge can be characterised by the three dimensions -
acquisition, application
and
ethics
. Acquisition relates to what has been found out using enquiry methods.
Application relates to how the findings can be put into practice (i.e. technology).
Ethics relates to the right and wrong ways to find out new things or to use technologies.
But doing science is influenced by the societal norms, which determines its legitimacy.
And making a tool to support impact assessment is more than putting science and
politics together.
Hence, a modelling system like the SEAMLESS Integrated Framework
(SEAMLESS-IF) should not be regarded as a strictly scientific/technical application,
but as a tool for communication between science and policy. Such interaction is a
discernible feature of impact assessment working procedures. It is therefore logical
that interaction starts already with
potential
users, which can contribute to the
development of the tool.
SEAMLESS is an integrated framework that enables simulation of effects of
agricultural and rural development policies and innovations, with a strong emphasis
on communication between scientists and stakeholders (Van Ittersum et al.
2008
a).
This means that impact assessments made by SEAMLESS-IF can be understood as
social processes, including but not restricted to their formal end products. A social
process perspective directs attention beyond the content of assessment reports and
encompasses questions regarding participation, presentation, evaluation, and how
the boundaries between the scientific and political dimensions of the assessment are
negotiated
and
legitimized
(Hoppe
2005)
.
A deliberative process is one in which values and facts are constructed within a
process where ideas are reciprocally confronted with one another as a means for
learning. In order for a deliberative process to be scientifically credible, it must
consider all forms of knowledge - science, expertise, local and indigenous. It must also
ensure the 'accountability' of each form of knowledge before relying upon it as a
foundation for political choices. To make the process work there must be full and
open access to knowledge by all participants. There must also be full transparency
in how knowledge is created and used and how values are discovered and applied.
In doing so, deliberative processes may address the twin problems of uncertainty and
ambiguity. This is done by institutionalizing two basic principles of organizational
learning - adaptation through experimentation and iterativeness through continuous
monitoring, evaluation, and change (Casey
2005)
.
Following Habermas, we could state that SEAMLESS-IF can contribute to a
deliberative impact assessment process, provided that the following conditions are
met: (1) The values of the organisation requesting an assessment meet those of the
SEAMLESS-IF. (2) The problem definition can be debated between involved parties.
(3) The outcome of the assessments allows for a real debate with affected stakeholders.
The third condition will normally not be in the hands of the “model owners” but
controlled by the policy agencies that are using the SEAMLESS framework.
To match the first condition, we compare if the policy experts' assumptions about
science-policy nexus, are compatible with the hypotheses set in SEAMLESS-IF.
To meet with the second one, we illustrate how the problem definition created a real
debate between policy experts and integrative modellers in the regional test cases.
