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Predicting Voting Patterns in the General Assembly 1

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  • Vincent, Jack E.

Abstract

This project attempts to relate a large number of potential predictors to voting data generated at the United Nations. Numerous associations were found when the predictors, 77 in all, were related to 13 different kinds of voting scores. Because of considerable redundancy in both sets of data, national attribute and voting, the results were factor analyzed and the original variables were reduced to 14 sets of factor scores representing the national attribute data, and 4 representing the voting data. Several significant associations emerged from the intercorrelation of these two sets of factor scores, with the independent variables “Economic Development,” “Democracy,” and “U.S. Relations” exhibiting considerable predictive power. When the overall relationships between the two sets of data were assessed by use of the canonical correlation technique, “Economic Development” received the greatest weight on the national attribute side, and “Eastern Voting” on the voting (dependent variable) side. These findings accord well with previous research, in that “Economic Development” seems to predict negativism as revealed by voting. Thus “Economic Development” appears to be fundamentally related to certain schisms at the United Nations, with the representatives from the most developed states appearing the most “negative” as evidenced by questionnaire responses and voting behavior. Such orientations are likely to have a significant impact on the evolution of the organization. At a theoretical level, the present findings may have considerable relevance for both Social Field theory and Attribute theory.

Suggested Citation

  • Vincent, Jack E., 1971. "Predicting Voting Patterns in the General Assembly 1," American Political Science Review, Cambridge University Press, vol. 65(2), pages 471-498, June.
  • Handle: RePEc:cup:apsrev:v:65:y:1971:i:02:p:471-498_13
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    Cited by:

    1. K. Macdonald, 1976. "Causal modelling in politics and sociology," Quality & Quantity: International Journal of Methodology, Springer, vol. 10(3), pages 189-208, September.

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