² See: Permanent Missions to the United Nations, United Nations Document, ST/SG/SER.A/186, 01, 1966 Google Scholar.

³ It is possible that many more of the responding delegates were also Ambassadors. It is probably desirable to have as many Ambassadors as possible within the group of responding delegates, but, as the project has been set up, this is not necessary. That is, as explained above, the major purpose of the project is to relate non-personal data to delegate response patterns. A delegate's “rank,” then, is considered to fall in the same analytical category (personal) as “age,” “education,” etc. These are potentially fruitful lines of inquiry, but are not pursued here for reasons explained above.

⁴ Banks, Arthur S. and Textor, Robert B., A Cross Polity Survey (Cambridge: M.I.T. Press, 1953) pp. 54–117 Google Scholar.

⁵ Phillip K. Gregg and Arthur S. Banks, “Dimensions of Political Systems: Factor Analysis of A Cross Polity Survey,” this Review, 59 (1965), p. 607.

⁶ Zetterberg, Hans L., On Theory and Verification in Sociology (Totowa, New Jersey: The Bedminster Press, 1963), pp. 54–55 Google Scholar.

⁷ A panel of 51 upper division international relations students at Florida Atlantic University were asked to judge the statements.

⁸ Technically, then, it is movement away from the mean value, not actual agreement or disagreement with the judges, which defines “positive,” “dynamic,” “negative” and “static” attitudes. Thus, whenever a subject deviates from the central tendency, he is viewed as evincing one of these kinds of attitudes, “Attitude” is employed here in a broad sense to include “feelings,” “perceptions,” and “desires.” A respondent having a score exactly equal to the mean value, of course, does not evidence either a “negative,” “static,” “positive,” or “dynamic” attitude.

⁹ Reliability, of course, refers to the characteristics of an entire test instrument and not its individual items. Because of the decision to work with individual items and not an aggregate score in this study, the above estimate is given simply for informational purposes.

¹⁰ Banks and Textor, op. cit. Selection of the 34 variables from the total of 57 treated by Banks and Textor was based upon the possibility of constructing a scale with direction for each variable, although in some cases, it is a nominal one, i.e., religious homogeneity (two categories). Also considered was the relative absence of ambiguous codings for the responding delegations. Although many of the Banks and Textor variables are soft, i.e., partially or completely subjective, nevertheless it has been successfully demonstrated that they are amenable to factor analysis and the factors tend to agree, in some respects, with other analysis of state social, economic, and political variables. See Gregg and Banks, “Dimensions of Political Systems …” op. cit., p. 607. The preference for the Banks and Textor variables over “hard” data collections, particularly over the excellent data in Russett, Bruce, et al. World Handbook of Political and Social Indicators (New Haven: Yale University Press, 1964)Google Scholar, lies in the fact, as explained by Arthur S. Banks and Phillip M. Gregg, that, “Despite the focus implied by the title, [World Handbook] most of the data series in this collection are of limited political significance.” Banks, Arthur S. and Gregg, Phillip M., “Grouping Political Systems, Q Factor Analysis of A Cross Polity Survey ,” The American Behavioral Scientist, 9 (1965), p. 6 CrossRefGoogle Scholar. In addition, the World Handbook's value was limited simply because data was not included for many of the responding delegations. For example, the World Handbook only covers 41 cases in respect to the expenditure of central governments as a ratio to gross national product; 18 cases in respect to employment by the general government and public enterprises; 44 cases in respect to votes for the Communist Party as percentage of total votes; 74 cases in respect to death by domestic violence per one million, through the years 1950–1962; and, 88 cases in respect to military personnel as a percentage of the total population. The N's for the Banks and Textor variables are, in most cases, considerably larger than this.

¹¹ United Nations delegate size was taken from Permanent Missions to the United Nations, op. cit. Time in the United Nations was scored by the number of years a respondent's state had been in the United Nations by December, 1965. Intergovernmental memberships were taken from Sachs, Mosche Y., ed., Worldmark Encyclopedia of the Nations, Vol. I (New York: Harper & Row, 1963), pp. 247–265 Google Scholar. Alliance scores are explained above. Military size (total men under arms) was taken from Worldmark Encyclopedia of the Nations, op. cit., Vol. 2–5, and supplemented by 1966 Reader's Digest Almanac and Yearbook (New York: Reader's Digest Association, 1965)Google Scholar. Distances from the US, USSR, and China were based on the great circle distances to closest possible points between states (states with mutual borders with the US, USSR, and China were coded 0). Percent urbanization was taken from Worldmark Encyclopedia of the Nations op. cit., Vol. 2–5. Ratio of people to schools was found by dividing a state's total number of schools into its total population. The number of schools was taken from UNESCO, Survey of World Education, Vol. 3 (New York: International Document Service, Columbia University Press, 1961 Google Scholar) and total population was taken from International Yearbook and Statesmen's Who's Who, 1966 (London: Burkes Peerage)Google Scholar. United Nations Emergency Force Pay and United Nations Pay were taken from House of Representatives Report, No. 1564, 89th Congress. Import and Export Figures to the United States were taken from 1965–66 issues of Overseas Business Reports (Washington: U.S. Printing Office)Google Scholar.

¹² Alker, Hayward R. Jr., and Russett, Bruce M., World Politics in the General Assembly, (New Haven: Yale University Press, 1965), pp. 30–31 Google Scholar.

¹³ The principal component solution was employed. Unities were placed in the principal diagonal of the correlation matrix and the factor matrix was rotated using Kaiser's varimax criterion. The minimum eigenvalue for which a factor was rotated was 1.0. See Harmon, Harry H., Modern Factor Analysis (Chicago: University of Chicago Press 1960)Google Scholar, Chapter 9; Kaiser, Henry F., “The Varimax Criterion for Analytical Rotation in Factor Analysis” Psychometrica, 23 (1958), 187–200 CrossRefGoogle Scholar; Kaiser, Henry F. “Computer Program for Varimax Rotation in Factor Analysis” Educational and Psychological Measurement 19 (1959), 413–420 CrossRefGoogle Scholar; Clyde, Dean J., Cramer, Elliott M., Sharin, Richard J., Multivariate Statistical Programs (Coral Gables, Florida: University of Miami, 1966), pp. 15–19 Google Scholar.

¹⁴ For applications of factor analysis in connection with United Nations voting see: Alker, Hayward R. Jr., and Russett, Bruce M., World Politics in the General Assembly, (New Haven: Yale University Press, 1965)Google Scholar; Bruce M. Russett, “Discovering Voting Groups in the United Nations,” this Review 60 (1966), 327–339; Hayward R. Alker, “Dimensions of Conflict in the General Assembly,” this Review, 58 (1964), 632–658. For other applications of factor analysis of interest, see: Russett, Bruce M., “Delineating International Regions,” Carnegie-IDRC Joint Study Group on Measurement Problems, Paper No. G60, Indiana University, 02, 1965 Google Scholar; Russett, Bruce M., International Regions and International Integration (Chicago: Rand-McNally, forthcoming)Google Scholar; Cattell, Raymond D., “The Dimensions of Cultural Patterns of Factorization of National Characters,” Journal of Abnormal and Social Psychology, 44 (1959), 215–253 Google ScholarPubMed; Cattell, Raymond D., Breul, H., and Hartman, H. Parker, “An Attempt at a More Refined Definition of Cultural Dimensions of Syntality of Modern Nations,” American Sociological Review, 17 (1951), 408–21CrossRefGoogle Scholar; Rummel, Rudolph J., “Dimensions of Conflict Behavior Within and Between Nations,” General Systems, Yearbook of the Society for the Advancement of General Systems Theory, Ann Arbor, Michigan, 1963 Google Scholar; Berry, Brian J. L., “Basic Patterns of Economic Development,” in Atlas of Economic Development (by Norton Ginsberg, Chicago, 1961) pp. 110–119 Google Scholar; Banks, Arthur S. and Gregg, Phillip M., “Grouping Political Systems, Q Factor Analysis of A Cross Polity Survey ,” The American Behavioral Scientist, 9 (1965), 3–6 CrossRefGoogle Scholar; Phillip M. Gregg and Arthur S. Banks, “Dimensions of Political Systems: Factoral Analysis of A Cross Polity Survey,” this Review, 59 (1965), 602–614; Tanter, Raymond, “Dimensions of Conflict Behavior Within and Between Nations, 1958–1960,” Journal of Conflict Resolution, 10 (1966), 41–64 CrossRefGoogle Scholar; and Rummel, R. J., “Dimensions of Conflict Behavior Within Nations, 1946–1959,” Journal of Conflict Resolution, 10 (1966), 65–73 CrossRefGoogle Scholar.

¹⁵ Factor scores were calculated using the formula: F=ZA (A′A)⁻¹ where F is an N×m matrix of factor scores, Z is an N×n matrix of scores on the original variables in standard score form, A is an n×m matrix of factor coefficients (loadings) and N = subjects, n = variables and m = factors. See Horn, John L. and Miller, Wilbur C., “Evidence on Problems in Estimating Common Factor Scores,” Educational and Psychological Measurement, 26 (1966), 617–622 CrossRefGoogle Scholar, for the advantages of this formula over other possible formulas, such as: F = ZA (defined above) or F = ZB where B is an n × m matrix in which unity is substituted for each “salient” coefficient and zero is substituted for every other loading. The most obvious advantage of the formula employed in this study is that it produces truly orthogonal factor scores, whereas the other formulas may not. In this connection, a check correlating each set of factor scores with every other set of factor scores showed them to be truly orthogonal with correlations of .0. See also Horn, John L., “An Empirical Comparison of Methods for Estimating Factor Scores,” Educational and Psychological Measurement, 25 (1965), 313–321 CrossRefGoogle Scholar, and Glass, Gene B. and Maguire, Thomas O., “Abuses of Factor Scores,” American Educational Research Journal, 3 (1966), 297–304 CrossRefGoogle Scholar.

¹⁶ The term “tends” must be emphasized because it is possible that a subject's very high score on one variable can “make up” for a deviation in the wrong direction on another variable. Nevertheless, an extensive visual check failed to reveal a single case where subjects with high factor scores on the factor dimensions did not have deviations on the means in the predicted “direction” on variables loading .30 or above on the factors.

¹⁷ The naming of factors is always arbitrary. Alker and Russett have argued, “Factors are not born with names but must be christened by their parents who may not be able to agree on what they should be called.” Alker and Russett, World Politics in the General Assembly, op. cit., p. 36. In fact, “factor names” may fall short of describing all of the variables loading most heavily on the factor. A listing of the heaviest loadings, then, makes it clear which are the important tests involved in producing factor scores. Simply referring to factor dimensions by their “name,” then, may not do complete justice to the actual loadings.

¹⁸ See Baggaley, Andrew R., Intermediate Correlational Methods (New York: John Wiley & Sons, 1964), pp. 21–23 Google Scholar. Once rank numbers were assigned, the Spearman correlational formula was employed for convenience. As Baggaley points out, the results of applying the Spearman formula to rank numbers is exactly the same as applying the Pearson formula to such numbers.

¹⁹ The opposite relationships are, of course, also true. That is, the lower a respondent's home state score is on the “Development Factor,” the stronger the respondent's dissatisfaction with the voting procedures of the Security Council. These generalizations may be stated in these terms because in almost all cases the answer marks ranged across the entire answer line. In those few cases where they did not, a statement such as “less satisfied,” instead of “dissatisfied,” is, of course, more technically true. In all cases, however, at least some of the respondents marked the “negative” or “static” sides of the answer lines (as indicated above).

²⁰ All significant correlations have been underlined. Because N is the same in every case, all correlations greater than ±.25 are significant at the .05 level or less, and all correlations ± .32 or above are significant at the .01 level or less. The generalizations that follow, then, are based upon these levels of significance. That is, every relationship is significant either at the .05 level or less. If the exact level is of interest, then it may be ascertained by reference to the table to see whether the correlation lies between ±.25 and ±.31, or is greater than +.32.

²¹ Technically, of course, it is more proper to say that economic development scores have a positive correlation with questionnaire scores However, because high questionnaire scores are assumed to connote negative behavior, the analysis is facilitated by stating the relationships in this way.

²² Shihata, Abraham P. I., “The Attitude of New States Toward the International Court of Justice,” International Organization, 14 (1965), p. 222 Google Scholar.

²³ Wilcox, Francis O., UN and the Nonaligned Nations, (New York: Foreign Policy Association, 1962), p. 54 Google Scholar.

²⁴ Babaa, Khalid I., “The ‘Third Force’ and the United Nations,” The Annals, 362 (11, 1965), 81–91 Google Scholar.

²⁵ Karefa-Smart, John, “Africa and the United Nations,” International Organization, 19 (1965), p. 766 CrossRefGoogle Scholar.

²⁶ Keohane, Robert Owens, “Political Influence in the General Assembly,” International Conciliation, No. 557 (1966), p. 5 Google Scholar.

²⁷ Manno, Catherine Senf, “Majority Decisions and Minority Responses in the UN General Assembly,” Journal of Conflict Resolution, 10 (1966), pp. 7–9 CrossRefGoogle Scholar.

²⁸ That is, such delegates have less, in the way of state capabilities, standing “behjncl” their wishes, desires and demands.

²⁹ Boulding, Kenneth, Conflict and Defense (New York: Harper Torchbook, 1963), p. 323 Google Scholar.

³⁰ Jensen, Lloyd, “Military Capabilities and Bargaining Behavior,” Journal of Conflict Resolution, 9 (1965), p. 163 CrossRefGoogle Scholar.

³¹ See: Nicholas, H. G., The Evolution of the Diplomatic Method (New York: Macmillan, 1954), p. 84 Google Scholar; Nicholas, H. G., The United Nations as a Political Institution (London: Oxford University Press, 1961), pp. 88–122 Google Scholar; Bailey, Sydney D., The General Assembly of the United Nations (New York: Frederick A. Praeger, 1960), pp. 8–18 Google Scholar; Best, Gary, Diplomacy in the United Nations (Northwestern University, 1960, unpublished dissertation)Google Scholar.

³² Crabb, Cecil B. Jr., American Foreign Policy in the Nuclear Age (Elmsford, N.Y.: Row, Peterson & Co., 1960), p. 442 fGoogle Scholar.

³³ Pederson, Richard F., “National Representation in the United Nations,” International Organization, 15 (1961), p. 258 Google Scholar.

³⁴ Ibid., pp. 258–264.