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||The deepest of the three sorts of uncertainty distinguished by Funtowicz and Ravetz (1990):
Inexactness, unreliability and border with ignorance. Our knowledge of the behavior of the
data gives us the spread, and knowledge of the process gives us the assessment, but there is still
something more. No process in the field or laboratory is completely
known. Even physical constants may vary unpredictably. This is the realm of our ignorance: it includes
all the different sorts of gaps in our knowledge not encompassed in the previous sorts of uncertainty.
This ignorance may merely be of what is significant, such as when anomalies in experiments are
discounted or neglected, or it may be deeper, as is appreciated retrospectively when revolutionary new
advances are made. Thus, space-time and matter-energy were both beyond the bounds of physical
imagination, and hence of scientific knowledge, before they were discovered. Can we say anything
useful about that of which we are ignorant? It would seem by the very definition of ignorance that
we cannot, but the boundless sea of ignorance has shores, which we can stand on and map.
The Pedigree qualifier in the NUSAP system maps this border with ignorance in knowledge production.
In this way it goes beyond what statistics has provided in its mathematical approach to the management of uncertainty.|
||Inderterminacy is a category of uncertainty which refers to the open-endedness (both
social and natural) in the processes of environmental damage caused by human intervention.
It applies to processes where the outcome cannot (or only partly) be determined from the input.
Indeterminacy introduces the idea that contingent social behavior also has to be included in the
analytical and prescriptive framework.
It acknowledges the fact that many knowledge claims are not fully determined by empirical observations
but are based on a mixture of observation and interpretation.
The latter implies that scientific knowledge depends not only on its degree of fit with nature (the observation part),
but also on its correspondence with the social world (the interpretation part) and on its success in building and
negotiating trust and credibility for the way science deals with the 'interpretive space'.
||One of the three sorts of uncertainty distinguished by Funtowicz and Ravetz (1990): Inexactness, unreliability and border with ignorance.
Quantitative (numerical) inexactness is the simplest sort of uncertainty; it is usually expressed by significant digits and
error bars. Every set of data has a spread, which may be considered in some contexts as a
tolerance or a random error in a calculated measurement. It is the kind of uncertainty that relates
most directly to the stated quantity, and is most familiar to student of physics and even
the general public. Next to quantitative inexactness one can also distinguish qualitative inexactness which
occurs if qualitative knowledge is not exact but comprises a range.|
||One of the seven types of uncertainty distinguished by De Marchi
(1994) in her checklist for characterizing uncertainty in
institutional, legal, moral, proprietary, scientific, situational, and societal uncertainty. Institutional uncertainty is in some sense a subset of societal
uncertainty, and refers more specifically to the role and actions of
institutions and their members. Institutional uncertainty stems from
the "diverse cultures and traditions, divergent missions and values,
different structures, and work styles among personnel of different
agencies" (De Marchi, 1994). High institutional uncertainty can
hinder collaboration or understanding among agencies, and can make the
actions of institutions difficult to predict.|
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