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Unionisation in a Comparative Neural Network Model: A Trade Union Membership Prediction in 12 States

NCJ Number
170592
Journal
Substance Use and Misuse Volume: 33 Issue: 3 Dated: (1998) Pages: 819-836
Author(s)
D Aprile
Date Published
1998
Length
18 pages
Annotation
Squashing Theory and the Artificial Neural Networks methodology were used to conduct an international comparison of the factors that determine the level of union membership in the most economically advanced countries.
Abstract
The research methods were designed to overcome the disadvantages of previous research based on the linear analysis of a restricted number of complex variables. The study examined 49 variables in 12 countries over a 12-year time period. The 12 countries were Austria, Denmark, France, West Germany, Italy, Japan, the Netherlands, Norway, Sweden, Switzerland, the United Kingdom, and the United States. The data covered various time spans within the period 1975-86. Results demonstrated that a few independent variables do not lead to the result; instead the total or approximate fuzzy participation of all the variables determine the result. Findings also indicated that the analytic technique raised more questions than it is capable of resolving, at least on the theoretical level. Further research is recommended. Figures, appended tables, author biography and photograph, and 22 references (Author abstract modified)

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