RESEARCH METHOD COHEN ok

246 INTERNET-BASED RESEARCH AND COMPUTER USAGE
has its roots in chaos theory and complexity
theory.
For Laplace and Newton, the universe was
rationalistic, deterministic and of clockwork order;
effects were functions of causes, small causes
(minimal initial conditions) produced small effects
(minimal and predictable) and large causes
(multiple initial conditions) produced large (multiple)
effects. Predictability, causality, patterning,
universality and ‘grand’ overarching theories, linearity,
continuity, stability, objectivity, all contributed
to the view of the universe as an ordered
and internally harmonistic mechanism in an albeit
complex equilibrium, a rational, closed and
deterministic system susceptible to comparatively
straightforward scientific discovery and laws.
From the 1960s this view has been increasingly
challenged with the rise of theories of chaos
and complexity. Central to these theories are
several principles (e.g. Gleick 1987; Morrison
1998, 2002a):
Small-scale changes in initial conditions can
produce massive and unpredictable changes
in outcome (e.g. a butterfly’s wing beat in
the Caribbean can produce a hurricane in the
United States).
Very similar conditions can produce very dissimilar
outcomes (e.g. using simple mathematical
equations: Stewart 1990).
Regularity, conformity and linear relationships
between elements break down to irregularity,
diversity and nonlinear relationships between
elements.
Even if differential equations are very simple,
the behaviour of the system that they are
modelling may not be simple.
Effects are not straightforward continuous
functions of causes.
The universe is largely unpredictable.
If something works once there is no guarantee
that it will work in the same way a second time.
Determinism is replaced by indeterminism;
deterministic, linear and stable systems are
replaced by ‘dynamical’, changing, evolving
systems and non-linear explanations of
phenomena.
Continuity is replaced by discontinuity,
turbulence and irreversible transformation.
Grand, universal, all-encompassing theories
and large-scale explanations provide inadequate
accounts of localized and specific
phenomena.
Long-term prediction is impossible.
More recently theories of chaos have been
extended to complexity theory (Waldrop 1992;
Lewin 1993) in analysing systems, with components
at one level acting as the building blocks
for components at another. A complex system
comprises independent elements which, themselves,
might be made up of complex systems.
These interact and give rise to patterned behaviour
in the system as a whole. Order is not
totally predetermined and fixed, but the universe
(however defined) is creative, emergent
(through iteration, learning, feedback, recursion
and self-organization), evolutionary and changing,
transformative and turbulent. Order emerges
in complex systems that are founded on simple
rules (perhaps formulae) for interacting organisms
(Kauffman 1995: 24).
Through feedback, recursion, perturbance, autocatalysis,
connectedness and self-organization,
higher and greater levels of complexity are differentiated,
new forms arise from lower levels
of complexity and existing forms. These complex
forms derive from often comparatively simple
sets of rules – local rules and behaviours generating
complex global order and diversity (Waldrop
1992: 16–17; Lewin 1993: 38). Dynamical
systems (Peak and Frame 1994: 122) are a
product of initial conditions and often simple
rules for change. General laws can govern adaptive,
dynamical processes (Kauffman 1995: 27).
There are laws of emergent order, and complex
behaviours and systems do not need to
have complex roots (Waldrop 1992: 270). Importantly,
given these simple rules, behaviour
and systems can be modelled in computer simulations.
It is important to note that the foundations
of computer simulations lie in complexity theory,
as this provides a response to the charge laid at