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such as for self-esteem, game theory preferences,
etc.). Moreover, the lack of a theory of measure-
ment at the individual level is amplified at the
group (Levine & Moreland, 1998), organization
(Pfeffer & Fong, 2005), and virtual organiza-
tion levels (Lawless et al., 2008b). How then
to represent interdependence among agents and
organizations? While this problem is ancient, with
threads running from Aristotle on thoughts about
objects to the perspective shifts of Copernicus
in the study of planetary motion, the mind-body
duality of Descartes, and the emotions-thoughts
complementarity of William James, our interest
is not historical but theoretical.
Traditional social and game theories, known
collectively as methodological individualism,
have been used to study interdependence for de-
cades. Game theory was one of the first to model
interdependence rationally and to solve it in the
laboratory for two sets of non-cooperative oppo-
nents. These “toy” problem solutions are known
as Nash Equilibria, which Luce and Raffa (1967)
believed resulted in unfair distributions of a game's
resources among its participants. Axlerod (1984)
concluded that the unfair distribution from “the
pursuit of self-interest” (p.7) in games could be
controlled with punishment sufficient to promote
“the evolution of cooperation”. But Luce and
Raiffa (1967) warned that it was unlikely that “any
sociology be derived from the single assumption
of individual rationality” (p. 196)
Indeed, outside of the laboratory, game theory
has not been validated (Safney, 2007) nor it has
produced satisfactory solutions (Schweitzer et
al., 2009). One problem with Nash Equilibria is
that they have been conceived as 2-D solutions of
games between opponents that largely overlook
their social effect on the population, which would
make it a 3-D problem and more realistic. Our
conservation of information model offers a new
theory for interdependence set in 3-D.
The general strategy of working with inter-
dependence in social science creates confounds
(Kenny et al. 1998), which has lead to the need to
remove or control the effects of interdependence
in the analyses of social data. For example, Dawes
et al. (1989) found that actuarial data of human
behavior were less immune to the effects of inter-
dependence and thus more reliable and valid than
clinical or forensic (expert) diagnoses of human
pathology. Our goal is the opposite as we have
tried to remove observer independencies to better
establish the science of interdependence in orga-
nization, system and social processes (Lawless et
al., 2009). For example, community oppression
under the leadership of an illegal gang and its gang
leaders may indicate over time and resources and
geospatially the variability in the power expended
by the gang to control one community's members
versus another's should indicate the costs of con-
trol, censorship, and violence.
In this new paper, we focus on interdepen-
dence and its application to the Department of
Energy (DOE), industry, and telemedicine and
e-health. In our field work with DOE, we have
found in the past that majority rule decision-
making generates more conflict but is faster and
produces qualitatively better decisions than does
consensus rule decision-making (Lawless et al.,
2008a). For industry, we have found that smaller
organizations are more unstable than larger ones,
a here-to-fore unsuspected reason for mergers
and acquisitions (Lawless et al., 2009). And for
telemedicine and e-health, we have speculated that
these new technologies will revolutionize health
care by expanding its reach, by modernizing its
delivery, and by holding down the inexorable rise
in its costs (Stachura et al., 2009).
While the Hawthorne effect - observing hu-
man workers affects their performance - is an old
finding (Roethlisberger & Dickson, 1939), the
problem was first recognized in social psychology
by Allport (1962) who concluded that the shift
from an individual to a social perspective was
the major remaining unsolved problem in social
psychology. Then at the end of his career, Kelley
(1992), as one of the first users of game theory in
social psychology, concluded that self-reported
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