Empirical research often lacks theory. This book progressively
works out a method of constructing models which can bridge the gap
between empirical and theoretical research in the social sciences.
This might improve the explanatory power of models. The issue is
quite novel, and it benefited from a thorough examination of
statistical and mathematical models, conceptual models, diagrams
and maps, machines, computer simulations, and artificial neural
networks. These modelling practices have been approached through
different disciplines.
The proposed method is partly inspired by reverse engineering.
The standard covering law approach is abandoned, and classical
induction restored to its rightful place. It helps to solve several
difficulties which impact upon the social sciences today, for
example how to extend an explanatory model to new phenomena, how to
establish laws, and how to guide the choice of a conceptual
structure.
The book can be used for advanced courses in research methods in
the social sciences and in philosophy of science.
General
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