414 Enabling Policies and Institutions for Sustainable Agricultural and Food Systems
employed. Global problems were approached as essentially economic and resource
based, resulting in limited parameters of concern focused largely on material and
energy flows. Population, and society in general, were seen as relevant only in so
far as they generated (or were affected by) these flows.
Models: the second generation
Efforts to look at the global environment/development picture have become more
sophisticated in the 1980s and 1990s. The authors analysed several studies from
researchers associated with the International Institute for Applied Systems Analysis
(IIASA) and the Worldwatch Institute, applying the same list of attributes used to
analyse the models. Table 20.2, above, includes the social visions contained in
pieces written in the 1980s by Lester Brown (Brown, 1981; Brown et al, 1990) and
by Clark and Munn (1986) on the prospects for a sustainable global future.
The pieces examined demonstrate a more complex view than the models but
share a similar focus. Like the modellers, Brown and his Worldwatch colleagues
concentrate on population, resources and material/energy flows. Explicit social
concerns are limited to an emphasis on lifestyle (presumably in industrialized
countries) and the argument that individual behaviour can reduce demand on
global resources. Broader social, organizational and structural issues are not
addressed. The Clark and Munn piece differs from the first-generation models in
its non-linear approach; greater concern with institutions; and the treatment of
uncertainty, surprise and discontinuities in the generation of knowledge and its
uses. The major concerns, however, remain population and resources, and no dis-
tinct social vision is generated.
Although sharing a similar focus with the early models, these more recent
efforts attempt to improve on earlier studies by acknowledging the role of uncer-
tainty and surprise in projections and by experimenting with other techniques,
such as backcasting and constructing future histories. The importance of surprise
was emphasized by the failed projections of some of the early models, and has
received significant recent attention (Glantz et al, 1998; Kates and Clark, 1996;
Schneider et al, 1998; Toth et al, 1989). Global systems theorists have come to
recognize that, for systems near thresholds of change, deterministic analysis no
longer works as the system becomes unpredictable and stochastic elements pre-
dominate, and inherent indeterminism sets in (see, for example, Gallopin and
Raskin, 1998). Research concerned with systems undergoing change must assume
the prevalence of discontinuous changes and surprise and be more concerned with
uncertainty than predictability. Perrings (1987, p11) distinguishes between ‘the
probabilistic uncertainty that assumes away our inability to foresee the effects of
our actions’ and ‘uncertainty before ignorance, novelty, and surprise ... [arising]
from the system’s existence in real, historical, irreversible time’. The time in ques-
tion is, in Georgescu-Roegen’s terms, not time (the mechanical measurement of an
interval) but rather Time (the continous succession of moments) (Perrings, 1987,
p111). Whereas statistical prediction may have some relevance in time, it has none