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A further note on the classification of political regions according to electoral behavior

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References

  1. Vittorio Capecchi and Giorgio Faini, A Classification of Italian Regions According to Electoral Behavior, in “Quality & Quantity”, II (1968), pp. 116–23.

  2. There is abundant literature on the nature of regional effects. See for example Kevin R. Cox, On the Utility and Definition of Regions in Comparative Political Sociology, in “Comparative Political Studies”, II (1969), pp. 68–98; Daniel Derivry and Mattei Dogan, Unité d'analyse et espace de reférence en écologie politique. Le canton et le département français, in “Revue française de science politique”, XXI (1971), pp. 517–70; and Leo Hazlewood and Dennis Paranzino, Regions, Regionalism and Violence: ‘Groups’ of Political Systems as Problems in Comparative Analysis, Paper prepared for delivery at the Annual Meeting of the International Studies Association, San Juan, Puerto Rico, March 17–20, 1971.

  3. Cox, op. cit., p. 69.

  4. See for example the work of Francois Goguel especially his Géographie des élections françaises de 1870 à 1951, Paris, 1951; and Modernisation économique et comportement politique, Paris, 1969. Geographical variations in the Italian vote have been discussed in Vittorio Capecchi and Giorgio Galli, Il comportamento elettorale in Italia, Bologna, 1968; Mattei Dogan and O. M. Petracca (eds.), Partiti politici e strutture sociali in Italia, Milano, 1962. The importance of regional contrasts in the mass politics of other European systems can be found in Erik Allardt and Yrjo Littunen (eds.), Cleavages, Ideologies and Party Systems, Helsinki, 1964; S. M. Lipset and Stein Rokkan (eds.), Party Systems and Voter Alignments, New York, 1967; and Erik Allardt and Stein Rokkan (eds.), Mass Politics, New York, 1970. See also Roger de Smet, La Géographie électorale en Belgique, in “Revue française de science politique” II (1952), pp. 87–95; and J. Stehouwer, Long-term Ecological Analysis of Electoral Statistics in Denmark, in “Scandinavian Political Studies”, II (1967), pp. 97–116.

  5. For a cross-national analysis of this problem see the collection of papers contained in E. A. G. Robinson (ed.), Backward Areas in Advanced Countries, London, 1969. See also Kevin Allen and M. C. MacLennan, Regional Problems and Policies in Italy and France, London, 1970.

  6. Cox, op. cit., p. 72. Regionalism is not the same as sectionalism. While certain political cleavages have been related to sectional differences in various Western European societies, others have been intersectional.

  7. Richard Hamilton, Affluence and the French Worker in the Fourth Republic, Princeton, 1967, p. 315.

  8. Capecchi and Faini op. cit., pp. 118–19.

  9. Prior to the general availability of computational equipment for rapid statistical processing of multivariate ecological data, most regional studies presented their results in cartographic form — a series of individual maps indicating with various degrees of shading the relative areal strengths of the political, social, economic or demographic variables under study. In most cases, it was entirely dependent upon the visual acuity of the reader to establish an association between the variables. This method did not allow for any reliable test or index of association between one variable and another, except the mere appearance of geographical coincidence. As Dogan and Rokkan have remarked with respect to such maps: “Variables tend to be judged by their immediate geographical covariation with the dependent variable rather than by their share in the total variance. There is no obvious cartographic equivalent of the partial correlation”. See Quantitative Ecological Analysis: Contexts, Trends, Tasks, in “Information sur les sciences sociales”, VI (1967), p. 43.

  10. On this point see Stein Rokkan and Henry Valen, Archives for Statistical Studies of Within-Nation Differences, in Rokkan (ed.), Data Archives for the Social Sciences, Paris, 1964, pp. 125–27.

  11. See Johan Galtung, Diachronic Correlation, Process Analysis and Causal Analysis, in “Quality and Quantity”, IV (1970), pp. 55–94.

  12. For a justification of the use of small ecological units within a larger ecological space of reference see Derivry and Dogan, op. cit. The choice of ecological unit has generated considerable controversy in the study of French electoral geography. For opposing viewpoints see Robert Arambourou, Réflexions sur la géographie électorale, in “Revue française de science politique”, II (1952), pp. 521–42; and Raymond Aron, Réflexions sur la politique et la science politique française, in “Revue française de science politique”, V (1955), pp. 5–20.

  13. This caveat derives from William S. Robinson's now famous critique of the “ecological fallacy”. See his Ecological Correlations and the Behavior of Individuals, in “American Sociological Review”, XV (1950), pp. 351–57. See also J. M. Beshers, Statistical Inferences From Small Area Data, in “Social Forces”, XXXVIII (1960), pp. 341–48. For a revisionist critique of Robinson see Raymond Boudon, Propriétés individuelles et propriétés collectives: un problème d'analyse écologique, in Raymond Boudon and Paul Lazarsfelf (eds.), L'analyse empirique de la causalité, Den Haag, 1966, pp. 191–219; and Otis D. Duncan, R. P. Cuzzort and B. Duncan, Statistical Geography: Problems in Analyzing Areal Data, Glencoe, 1961.

  14. As Boudon points out, even in studies employing very small homogenous spatial units, it is difficult to draw inferences about individual behavior on the basis of ecological or group properties. The question is not so much one of statistical analysis, but one of theory. The question of regional effects involves whether or not one assigns causality either to the “norms” of the milieu or its structural attributes. With respect to norms, we might hypothesize that individual behaviour is a function of individual perceptions of the frequency of this behavior in the milieu. We might also hypothesize that individual behaviors are a product of the sociological structure of the milieu. For example, does the propensity to vote communist vary as a function of one's perception of the anticipated results, thereby producing stability through habitual communist voting, or rather is it a function of the social structure (proportion of industrial workers in the milieu)? See Boudon, L'analyse mathématique des faits sociaux, Paris, 1967, pp. 165–88.

  15. Detailed breakdowns of socioeconomic and political data for small area units are not always possible for legal reasons and certain rules of secrecy. See Rokkan (ed.), Data Archives, p. 19; and Jean-Paul Trystram, Data Archives and Regional Planning in France, in “Information sur les sciences sociales”, V (1966), pp. 83–84. Capecchi and Faini were not able to quantify information on party organization at the commune level.

  16. Edwin K. Scheuch, Cross-National Comparisons Using Aggregate Data: Some Substantive and Methodological Problems, in Richard L. Merritt and Stein Rokkan (eds.), Comparing Nations, New Haven, 1966, pp. 132–34.

  17. Cf. Derivry and Dogan, op. cit.

  18. See Vincent E. McHale and John E. McLaughlin, Electoral Alignments, Regional Imbalances and Developmental Change in Postwar Italy, Paper prepared for delivery at the 1972 Annual Meeting of the Canadian Political Science Association, Montreal.

  19. See Kevin R. Cox, The Voting Decision in a Spatial Context, in Christopher Board, et al. (eds.), Progress in Geography, London, 1969, pp. 83–117.

  20. The question of whether or not to weight ecological units continually arises in spatial analysis, especially when the areal units display wide variations in size or demographic charcteristics. Some investigators have chosen to eliminate polar extremes from their analyses in order to avoid distortion and possibly disturbing influences (e.g. the elimination of Paris and Corsica from studies of electoral geography in France). Other investigators have deliberately included extreme cases, preferring instead to treat them as “outliers” or deviant cases. Simply moving to smaller areal units does not avoid this issue entirely. In their study of occupational and religious influences on votes for the French Left, Derivry and Dogan analyzed 2,477 cantons having active populations ranging from 400 to 32,800. Capecchi and Faini studied 7,144 Italian communes out of an approximate total 8,035. Italian communes vary demographically from those in excess of 500,000 inhabitants to those having less than 3,000. Because all spatial units are treated equally in most ecological studies, even in the face of extreme variability, the investigator is often tempted to assign proportional weights to the larger units to prevent the lesser units from overbiasing the results. We would argue that the issue of weigthing depends almost entirely upon the theoretical framework and the nature of the inferences one wishes to draw from the data. If one is primarily concerned with making statements about individuals on the basis of spatially-distributed summaries of individual attributes, then weighting the more populous units seems in order. Here the focus is on individual units and not the ecological units. Where ecological analysis is solely concerned with the properties and attributes of the spatial units themselves, then weighting is not an appropriate procedure. Here rather than drawing inferences about individual level behavior, the goal is to make statements about the interrelationship and patterning of the areal units. As Blalock notes, it must be assumed that the areal unit themselves are part of social reality, and as such constitute an important variable in the explanatory process. See his Causal Inferences in Non-experimental Research, Chapel Hill, 1964, pp. 95–126. See also A. H. Robinson, The Necessity of Weighting Values in Correlation Analysis of Areal Data, in “Annals of the Association of American Geographers”, XLVI (1956), pp. 233–36; and Edwin N. Thomas and David L. Anderson, Additional Comments on Weighting Values in Correlation Analysis of Areal Data, in Brian J. L. Berry and Duane F. Marble (eds.), Spatial Analysis: A Reader in Statistical Geography, Englewood Cliffs, 1968, pp. 431–36.

  21. See Giorgio Sandri, On the Logic of Classification, in “Quality & Quantity, III (1969), pp. 80–124.

  22. Hayward Alker, Jr., Mathematics and Politics, New York, 1965, pp. 80–85.

  23. A standard work on factor analysis for political and social research is R. J. Rummel, Applied Factor Analysis, Evanston, 1970.

  24. See Rummel, op. cit., chapter 19.

  25. An example of this application can be found in Cox, Geography, Social Contexts, and Voting Behavior in Wales, 1961–1951, in Allardt and Rokkan (eds.), Mass Politics, cit., pp. 117–59.

  26. See Cleavage Structures, Party Systems and Voter Alignments: An Introduction, in Lipset and Rokkan (eds.), Party System, cit., pp. 1–64.

  27. Val R. Lorwin, Belgium: Religion, Class and Language in National Politics, in Robert A. Dahl (ed.), Political Oppositions in Western Democracies, New Haven, 1966, pp. 147–87.

  28. Nicole Delruelle, René Evalenko and William Fraeys, Le comportement politique des électeurs belges, Bruxelles, 1970. This work summarizes a major effort to probe the moods and attitudes of the Belgian electorate in the wake of the electoral changes of 1965 and 1968.

  29. Data and analysis presented here have been extracted from McHale, A Note on the Transformation of Belgian Electoral Cleavages, Department of Political Science, University of Pennsylvania, 1972.

  30. See Delruelle et al., op. cit.

  31. See the selections in Giuseppe Di Palma (ed.), Mass Politics in Industrial Societies, Chicago, 1972.

  32. Sidney Tarrow, Economic Development and the Transformation of the Italian Party System, in Di Palma (ed.), op. cit., pp. 226–53.

  33. Data and analysis have been extracted from McHale and McLaughlin, Electoral Alignments, Regional Imbalances and Developmental Change in Postwar Italy, Paper prepared for delivery at the 1972 Annual Meeting of the Canadian Political Science Association, Montreal, Québec. This work contains a more detailed discussion of our findings along with the regionalization of Italian provinces according to a variety of political and socioeconomic indicators.

  34. For a description of economic growth in Italy after World War II, see Norman Kogan, A Political History of Postwar Italy, New York, 1966.

  35. See Dante Germino and Stefano Passigli, The Government and Politics of Contemporary Italy, New York, 1968, pp. 63–64.

  36. Mattei Dogan, Political Change and Social Stratification in France and Italy, in Lipset and Rokkan (eds.), Party Systems, cit., pp. 184–93.

  37. See Sandra Shaber, Socioeconomic Development and Political Behavior: Protest in Contemporary France, Paper prepared for delivery at the 1971 Annual Meeting of the Northeastern United States Political Science Association, Saratoga Springs, New York.

  38. Our findings show little significant variation from those reported by Capecchi and Galli in Il comportamento elettorale in Italia. For comparable indicators the relationships are in the same direction. Most of the correlations reported by Capecchi and Galli are quite low, and no controls were introduced for the operation of other variables in the relationship (partial correlations). There is no way of accounting for the amount of variance contributed by each ecological variable. Despite these deficiencies, the Capecchi and Galli work stands as a pioneering effort in probing the ecological bases of the Italian party system.

  39. Tarrow, op. cit., p. 239.

  40. Ibid., p. 241.

  41. Ibid., p. 234.

  42. Dogan, Le comportement politique des Italiens, in “Revue française de science politique”, IX (1959), pp. 398–402.

  43. See Kogan, The Government of Italy, New York, 1967, p. 44; and Germino and Passigli, op. cit., p. 119.

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  1. Vincent E. Mc Hale
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  2. John E. Mc Laughlin
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This article is derived from a larger continuing research project dealing with the comparative sociology of Western mass politics. We wish to express our gratitude to Dr. Henry Wells, Director of the Rena and Angelius Anspach Institute for Diplomacy and Foreign Affairs at the University of Pennsylvania, for making available certain research facilities during the computational phase of this study. We also wish to acknowledge the counsel of our colleagues Dennis Paranzino and Sandra Shaber.

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Mc Hale, V.E., Mc Laughlin, J.E. A further note on the classification of political regions according to electoral behavior. Qual Quant 6, 303–325 (1972). https://doi.org/10.1007/BF00211910

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