CREST Social Cleavages, Attitudes and Voting Patterns: A Comparison of Canada and
Transcription
CREST Social Cleavages, Attitudes and Voting Patterns: A Comparison of Canada and
CREST CENTRE FOR RESEARCH INTO ELECTIONS AND SOCIAL TRENDS Working Paper Number 81 September 2000 Social Cleavages, Attitudes and Voting Patterns: A Comparison of Canada and Great Britain By Robert Andersen and Anthony Heath The Centre for Research into Elections and Social Trends is an ESRC Research Centre based jointly at the National Centre for Social Research (formerly SCPR) and the Department of Sociology, University of Oxford http://www.crest.ox.ac.uk ABSTRACT This paper develops a novel method for comparative research on social cleavages that integrates the three major approaches to voting behaviour—the sociological approach, rational choice theory and the party identification model—under a single theoretical paradigm. We apply this integrated theory to the major regions of the USA, Canada and Great Britain. We find striking national and regional similarities in the effects of social group memberships on attitudes, but considerable diversity in the effects of social group membership on vote. Race is a notable exception—it deviates in the absence of uniformity of its effects of the cleavage on both attitudes and vote. That we find significant regional differences within countries suggests the importance of using region, rather than country, as the unit of analysis. These findings also underline the importance of paying close attention to political context when assessing the effects of social groups on voting. INTRODUCTION Most striking about the voting behaviour literature is that it groups neatly according to three paradigms—the sociological approach, party identification models and rational choice theory. Although there have been some attempts to integrate party identification within a rational choice framework (see, for example, Fiorina, 1981; Achen, 1992; Gerber and Green, 1998), for the most part researchers have tried to explain voting behaviour using only one of the approaches and have decidedly ignored the others. In fact, these approaches are almost universally treated as incompatible. We suggest that all of the approaches have merit and limitations, and that they should be seen as complementary rather than as opposing. We argue that each approach is applicable under different conditions of political context (e.g., different party competition structures and strengths of social cleavages). The best way to understand general patterns of voting is to integrate these approaches, and apply them in comparative analysis, paying careful attention to varying political contexts. Aside from these theoretical considerations, research on voting behaviour typically falls ill to other problems. First, if there are regional differences within a country, the common practice of using country as the unit of analysis in comparative research can average out the effects of social cleavages on attitudes and vote, masking their true impact. Secondly, single studies in political sociology often examine the impact of only one cleavage despite that including other groups is important if there are political parties representing their interests. Finally, the common practice of specifying social group variables and attitudinal measures as explanatory variables in a single model of voting behaviour ignores that attitudes are largely influenced by social group membership (see Bartle 1998, for a good discussion of this problem), and thus weakens the grouprelated coefficients since they account only for direct effects. The primary aim of this paper is to integrate the major approaches to voting behaviour in a comparative context. To accomplish this goal we develop a novel approach and method for comparing attitudes and voting in different societies. We make a number of distinctive moves. First, we focus on regional differences within countries, as well as on the usual national differences. Secondly, we break from convention by examining the relative impact of many social cleavages rather than exploring the effects of a single cleavage. Thirdly, rather than include attitudes as mediating variables within a single model, we use separate models to explicitly compare the effects of group identities on attitudes and vote. Finally, we develop a graphical technique for comparing the pattern and magnitude of relative social group effects on both attitudes and voting in different societies. Our method is an advancement over previous research because it allows sensible comparison of the relationship between social group variables and attitudes and vote across societies, even if datasets with non-identical measures are used. THEORETICAL BACKGROUND Sociological Approach to Voting The sociological approach to voting behaviour emphasizes the impact of social structure, suggesting that social group memberships influence voting choices (see for example, 1 Lazarsfeld et al.,1944; Alford 1967, Rose and Urwin 1969, 1970, Lijphart 1979, 1980). Voters are considered to be instrumental—i.e., they vote for parties that best reflect the interests of their groups. The origins of this approach can be traced to the Columbia school which carried out the first systematic surveys of the American electorate (see Lazarsfeld et al.,1944). These early studies stated the conditions for persistent group voting as the following: In sum, the conditions underlying persistent voting cleavages seem to be (1) initial social differentiation such that the consequences of political policy are materially or symbolically different for different groups; (2) conditions of transmitability from generation to generation; and (3) conditions of physical and social proximity for continued in-group contact in succeeding generations (Berelson, Lazarsfeld and McPhee 1954:75). Another influential work fitting under the sociological paradigm is that of Lipset and Rokkan (1967) who argued that not only do group identities influence voting behaviour, but that cleavage structures determine the number of political parties in a given polity. In other words, political parties evolve in response to the interests of social cleavages. The sociological approach, then, holds that group identities affect attitudes and interests. These attitudes in turn affect how people vote. By implication in any given society the effects of group membership should be the same on attitudes as they are on vote. It is difficult to deny the existence of social cleavages and their potential effects on attitudes and voting. However, this approach is unable to explain why cleavages such as social class have stronger relationships to attitudes and vote in some countries than others (see an edited volume by Evans, 1999). Party Identification Model Unlike the sociological model, the party identification model assumes voters to be expressive rather than instrumental, and attitudes and issue preferences are considered to be endogenous to vote. This approach holds that voters have long-standing psychological ties to specific political parties, and seldom waver from voting for them (Belknap and Campbell 1952, Campbell et al., 1960, Converse 1964). These party attachments are largely due to early socialization, reflecting mostly family influences. Simply put, people are influenced by the partisanship of their parents. The party identification model can be seen as similar to the sociological approach in that partisans “come to see themselves as members of social groups (e.g., Democrats, Republicans), in much the same way that certain people incorporate religious, regional, or ethnic groups into their self-conceptions” (Gerber and Green, 1998:794). On the other hand, unlike the sociological model, it holds that causation runs in both directions between attitudes and vote. As Campbell et al. (1960:128) state, “In the competition of voices reaching the individual the political party is an opinion-forming agency of great importance. The strength of relationship between party identification and the dimensions of partisan attitude suggests that responses to each element of national politics are deeply affected by the individual’s enduring party attachments.” This implies that the relationship between group membership and attitudes should be similar to that between group membership and vote. We could expect, however, that different political contexts 2 would induce different relationships between groups and attitudes than expected by the sociological approach. The party identification approach has been quite successful when applied to the two-party system of the US for which it was developed and where recent research has reaffirmed that partisanship is highly stable over time for the adult population (Green and Palmquist, 1990, 1994). It has been less successful elsewhere, in particular in Britain, where voters are less likely to make distinctions between their vote choice and partisan dispositions (Butler and Stokes, 1974). Rational Choice Although instrumental like the sociological model, the rational choice approach is much more individualistic, suggesting that voting decisions are based on cost-benefit analyses where voters match their individual issue preferences with party platforms. As Olson (1965:51) states, “only a separate and ‘selective’ incentive will stimulate a rational individual in a latent group to act in a group-oriented way.” According to Downs (1958:39), if the voter “is rational, he knows that no party will be able to do everything that is says it will do. Hence he cannot merely compare platforms; instead he must estimate in his own mind what the parties would actually do were they in power.” According to the rational choice approach, then, policy preferences are exogenous, but vote choices depend on the interplay between voters’ preferences and parties’ policy positions. Despite its individualist emphasis, the rational choice approach is not necessarily incompatible with either the sociological and party identification approaches. Although not explicit, rational choice theory allows for the possibility that social identities play a role in voting decisions since individual preferences can be determined by one’s position in society. Moreover, not all rational choice theorists discount party attachments. Rather than see them as influencing attitudes, however, these attachments are considered to represent ongoing tallies of assessments of party performances (see Fiorina, 1981). Although social groups may affect attitudes, this does not mean that voting decisions are made solely on the basis of these group-determined attitudes. Accordingly, the rational choice model implies that the relationship between preferences and vote will vary across different political contexts: if voters are given different political options from which to choose, then the relationship between attitudes and vote may also vary. Towards an Integrated Theory The three major approaches to voting behaviour can be integrated in a single theoretical framework. We start with the basic premise that voters are rational actors. We then adopt the sociological approach by arguing that attitudes are influenced by the groups to which one belongs. As we suggest earlier, this is not incompatible with the notion that voters are rational actors since their individual preferences at least partly reflect their position in social structure. We are not suggesting that social groups are homogenous in terms of attitudes and interests, only that social identities influence how people see the world (see Jenkins, 1996; Reid and Deaux, 1996). 3 If voters are rational actors we should expect that their electoral choices will reflect the concerns of the groups to which they belong. If these groups have a strong political presence—i.e., a viable political party represents their concerns—then voters will be inclined to vote for them. On the other hand, if the social group is not clearly represented by a particular party, voters will have no satisfying vote choice. Voters are then forced to choose a party that does not represent the interests of at least one of their group identities. Here the party identification model becomes relevant. Over time these voters, and their offspring, may identify with the party and its platform, taking on attitudes that seemingly do not reflect their group’s position in social structure. In such cases, vote and attitudes would still be highly related—e.g., right-wing voting will be associated with right-wing attitudes—since attitudes are affected by the platform of the party voters support. Let us now consider the situation where a particular party does represent the interests of a social group identity, but it also represents the interests of another opposing social identity. By way of an example, we briefly discuss a conflicting religious identity and social class identity. Assume a polity with a political party that is both secular and pro-working class. Suppose that no other parties represent the working class, but that other parties represent religious interests. In this situation, highly religious working class people may decide against voting for the working class party since it goes against their religious concerns. Likewise, those who do not belong to a religion, and hence are opposed to policies reflecting religious interests, may vote for the party regardless of their social class. In such cases, the attitudes of the working class may still be generally more left than those of other classes, but they may not necessarily be more likely to vote for the left-wing party. Simply put, vote is most likely to deviate from attitudes when a social identity is represented by a party, but that party also represents a conflicting identity. In summary, we are suggesting that voters are rational actors who try to maximize their utility. This utility is largely based on their position in social structure. Position in social structure is determined by membership in many, often competing, social groups (for a discussion of multiple social identities, see Stagnor, Duan and Glass, 1992; Deschamps and Doise, 1978). If there are no parties representing the interests of a particular social group, voters are forced to choose from other parties that represent other social group interests. If there is only one acceptable party though not a perfectly matching party, voters may adopt attitudes and policy preferences that reflect that party’s platform in the long term. If, on the other hand, the social group’s interests are reflected in a party platform, but a conflicting social group interest is also met, voters may be inclined not to vote for that party. In this case, attitudes will still reflect social group interests, despite that vote apparently does not. The present paper applies this integrated theory to voting behaviour in the major regions of Canada, Great Britain and the USA. Hypotheses Although our analysis controls for the impact of gender and education, we do not discuss these variables in detail because of space constraints. Our focus is on the relative impact of age, race, religiosity and social class. We evaluate four hypotheses based on our integrated theory: 4 1) In all regions, compared with the young (those under 30 years old), the elderly (those over 65 years old) are more authoritarian and more likely to vote for rightwing parties. A significant body of research shows political attitudes to be more resistance to change as people age (Alwin and Kosnick, 1991; Glenn, 1980; Jennings and Markus, 1984; Markus, 1979), with people be coming more socially conservative (see, for example, Park, 2000). In none of the regions we examined is there a party that uniquely represents the old, but the party structures are all similar in that there are distinct right-wing (socially conservative) parties with similar authoritarian platforms. We expect, then, that these authoritarian attitudes will be reflected in a greater propensity for seniors to vote for right-wing parties. 2) In all regions, compared to whites, visible racial minorities are more left in terms of attitudes and vote. The basis for this hypothesis is that ethnic minorities are more likely to be discriminated against in the job market and elsewhere than others. It follows that left-leaning policies, such as laws ensuring equal opportunity and income redistribution, are in the interest of racial minorities. Since it is rational to want to improve one’s position, one would expect racial minorities to be generally more left-leaning in terms of attitudes and vote than the majority population. 3) Those who regularly attend religious services are more authoritarian and more likely to vot e for right-wing parties than those who seldom or never attend religious services. Considering that religions are usually socially conservative to at least some degree (e.g., they are usually anti-abortion, anti-gay rights, pro-censorship etc.), it is sensible to expect that only those who hold similar attitudes would regularly attend religious services. Although none of the regions under study have parties specifically representing religious interests, in every region the right parties are more likely to cater to the religious than any other parties. 4) Unskilled labourers are more left in terms of attitudes than managers. If there are viable left parties, we would expect these attitudes to be reflected in left -voting. Because of the lack of a strong labour party in the US, we expect US regions to deviate from this pattern, perhaps exhibiting a pattern akin to the party identification model. It is clear that the material interests of the working class and managers are quite different (e.g., the working class is certainly more likely to depend on social programs). A great deal of recent research has shown that, while the relationship may be weakening, class is still significantly related to voting (see an edited volume by Evans, 1999; Lambert and Curtis, 1993). 5 DATA AND METHODS Data We use data from the 1997 Canadian Election Study1 (CES), the 1997 British Election Study (BES), the 1999 Welsh Assembly Election Study (WAES) and the 1996 American National Election Study (ANES). The CES is a representative rolling cross-sectional sample of all Canadians over the age of 18 during the 36-day official election campaign. Respondents were selected using random-digit-dialing and interviewed over the telephone. The total sample size is 3949, of which 3170 respondents were re-interviewed in a post-election survey2. Since most of the questions of interest to this study were asked only in the post-election survey, our results are based on this portion of the sample. We divide the CES data according to five regions (sample sizes after removing missing cases are in parentheses): West (890), Ontario (596), Quebec (681); East (290) and North (117). The BES is a representative sample of all British adults aged 18 or over living in private households. Respondents were selected using the Postcode Address File and interviewed face-to-face in their homes shortly after the May 1997 election. The total sample size is 3615, of which 3093 completed and returned a self-completion survey3. Since the items necessary to construct attitude scales were included only in the selfcompletion questionnaire, our analysis is based on this portion of the sample. We supplement the BES data with the WAES because the BES interviewed only 182 people in Wales. The WAES is similar in structure to the BES and all items used in this study were measured identically in both studies. The WAES has a sample size of 686, thus giving substantially more power to our statistical models of Wales. Respondents were interviewed in-home in May and June of 1999. The British data are divided into five regions (sample sizes omitting missing cases are in parentheses): Scotland (752), Wales (1040), North England (611); Midlands England (595) and South England (976). The ANES is a nationally representative sample of the American electorate. The ANES has a total sample size of 1714 respondents who were interviewed before the 1996 Presidential election; 1534 of these were re-interviewed in a post-election survey during November and December 1996.4 We restrict our analysis to the post-election survey. Respondents to the post-election survey were randomly allocated to face-to-face and 1 Data from the 1997 Canadian Election Survey were provided by the Institute for Social Research, York University. The survey was funded by the Social Sciences and Humanities Research Council of Canada (SSHRC), grant number 412-96-0007 and was completed for the 1997 Canadian Election Team of Andre Blais (Université de Montreal), Elisabeth Gidengil (McGill University), Richard Nadeau (Université de Montreal) and Neil Nevitte (University of Toronto). Neither the Institute for Social Research, the SSHRC, nor the Canadian Election Survey Team are responsible for the analyses and interpretations presented here. 2 The response rate for the campaign sample of the CES was 59%; The response rate for the post-election re-interview was 80% (Northrup 1998). 3 The total response rate for the in-home personal interviews of the BES was 62%; the response rate for the self-completion portion of the study was 53% (Thomson, Park and Brook, 1999). 4 Of these 1534 respondents, 1197 were initially interviewed in the 1994 election study; 337 were freshly sampled. The response rate to the pre-election survey was 71%. The response rate to the post-election reinterview was 90%. 6 telephone interviews. Limitations in sample size dictated that we used all respondents regardless of whether they were administered a personal or telephone interview. The ANES data are divided into the US Census’s five major regions (samples sizes omitting missing cases are in parentheses): Northeast (233), North Central (415), South (572) and West (312). Response Variables There are two dependent variables for our attitudes models—left-right attitudes and libertarian-authoritarian attitudes—both of which are operationalised as Likert-scales (Details of the scales are in Appendix A).5 The left-right scale measures positions on government intervention in the economy, specifically where one stands between socialism and laissez faire. Those who score low on the left-right scale favour government intervention, social spending and greater wealth redistribution; those who score high favour a freer economy. Libertarian-authoritarian attitudes are related to personal freedom of thought, association and lifestyles. Those who score high on the libertarian-authoritarian scale are more authoritarian in their views, while those who score low are more tolerant of alternative lifestyles and attitudes. The vote models have two dichotomous dependent variables: left vote versus other, and right vote versus other. In all Canadian regions the right parties consist of the Progressive Conservative Party and the Reform Party. The New Democratic Party (NDP) is the only party coded as left in all Canadian regions except Quebec, where the left-nationalist Bloc Quebecois is also included in the analysis of left vote.6 Although it received more votes than any other party in 1997, the Liberal Party is included as part of the “other” categories for our analysis because it can be considered a catchall party that occupies the centre of Canadian politics. In Great Britain, the left is occupied by the Labour Party and the right party is the Conservative Party. The national parties in Scotland and Wales, the Scottish National Party and Plaid Cymru respectively, were included in the other vote categories. In 1997 the Liberal Democrats were still considered the centralist party and thus are included in the “other” party category. Although there is arguably no left party in the US, we followed convention by treating the Democrats as the left party and the republicans as the right party (see Hout, Manza and Brooks, 1999). This practice is justified on the grounds that the Democrats are considerably more left and libertarian in terms of platform than the Republicans. Explanatory Variables In all regions gender is treated as a dummy variable with men coded as the reference category. Age is divided into four categories: less than 30 years old, 30-45, 46-64 and over 65 which is the reference category. With the exception of Scotland, for all Canadian and British regions race is operationalised simply a visible ethnic minority or white (the 5 Research on Britain (Heath, Evans and Martin, 1993) and the USA (Fleishman, 1988) have found these two attitudes are the major attitudinal dimensions. 6 Only 9 respondents in Quebec stated that they voted for the NDP, meaning that the non-nationalist left could not be analysed separately from the Bloc Quebecois. 7 reference category). The small number of nonwhites in Scotland prohibited including this variable for models of that region. For all US regions, race is divided into three categories: black, Hispanic and white (reference category). Religiosity is divided into two categories: those who attend church at least once a month (coded 1), and others (coded 0).7 Education is treated as a categorical variable with those without qualifications (or unrecognised foreign qualifications) being the reference category. In Canada and the US, the dummy variables for education are: (1) high school, (2) some post-secondary, and (3) university degree. In Great Britain the dummy variables represent (1) CSE or O-level, (2) A-level, (3) some post-secondary, and (4) university degree. Following from Hout, Manza and Brooks (1999) social class is divided into the same five categories for all regions: managers, professionals, clerical workers, skilled manual labourers and, semi- and unskilled manual labourers. Due to a significant portion of missing cases in most regions, a six category representing all those whose occupations are unknown is included in the models. STATISTICAL MODELS Attitudes are regressed on social group variables using ordinary least squares (OLS) regression. Probit models are used to regress vote on the same social group variables. We adjust the coefficients from the OLS models of attitudes in order to standardized the regression equations, making them comparable with the corresponding coefficients from the probit models of vote. We then explore the relationship between social groups, attitudes and votes across societies using scatterplots, plotting the coefficients from the attitudes model on the horizontal axis and the coefficients from the vote model on the vertical axis. We provide greater details of the method below. We start by discussing the probit models of left and right vote.8 The general probit model assumes that a binary dependent variable, y (1,0), represents a continuous latent variable, Z. For each combination of predictors there is a different mean ì , which represents the cut-off point where Z > 0 (the point where the observed discrete response variable changes from 0 to 1). In our case, Z represents the “propensity” to vote for left (or right) and y represents left vote (or right vote). The probit model assumes that the errors are independent and normally distributed and that the residual variance of the model equals one (Fox, 1997: 447). As we shall see later, that the residual variance is equal to one is a desirable property for our purpose of comparing different regression models. The basic probit model is as follows: 7 It would be substantively more interesting to split religiosity according to religion as well. Unfortunately, however, there were too few cases to make any such analysis sensible. 8 To determine whether there were significant differences in social group voting, we initially fit multinomial logit models (see Fox, 1997, Sections 15.2 and 15.3). It makes little sense to continue without evidence that social groups vote as blocks to at least some degree. Likelihood ratio tests showed that there were indeed group differences, suggesting that we could proceed to examine the effects of social cleavages on vote for the different types of left and right parties using probit models. 8 π i = Φ (α + β 1x i 1 + β 2 x i 2 + ... + β k x ik ) Where π i represents the probability that y =1 (in our case, vote for the party), Φ is the normal cumulative distribution function and (α + β 1 x i 1 + β 2 x i 2 + ...β k x ik ) represents the mean of Z given x 1 , x 2 + ... + x k . The â’s represent the slopes of the social group variables. â1 can be interpreted as the increase in Z for a one unit increase in x1, holding all other x’s constant. We now turn to the standardization of OLS models of attitudes. A simple way of standardizing regression equations so their coefficients can be compared is to constrain the mean squared error (MSE) for the two models to be equal. Recall that an assumption of the probit model is that the residual variance, and hence the MSE, of Z |x1, x2… xk is equal to 1. After fitting the OLS models, we can adjust the coefficients and standard errors so that the MSE of the model equals 1 using the following formula: β Adjusted β = MSE SE (β ) Adjusted SE (β ) = MSE While this adjustment is arbitrary from a substantive point of view, it is sensible considering that our dependent variables, the left-right scale and libertarian-authoritarian scale, have artificial metrics. Although we have different measures of attitudes in each of the data sets, meaning that we can not determine differences in attitudes across societies, this method allows us to directly compare the relative strength of social cleavages on attitudes and vote across societies. By way of clarification, let us use gender as an example. Our method cannot determine in which society women are most libertarian, but it can show in which societies the impact of gender on attitudes and vote is strongest. Rather than simply examine the tables of the coefficients from these models, which is not conducive to determining patterns of association when there are many regions under analysis, we can graph them on scatterplots, allowing us to clearly visualize the impact of social groups on attitudes and vote across regions. Figure 1 explains how these graphs are to be interpreted. The horizontal axis represents the attitude of the adjusted coefficient from the attitudes model; the vertical axis represents the attitude of the corresponding coefficient from the probit model of vote. If a social cleavage affects attitudes and vote similarly across regions (as implied by the sociological approach), the data will be in the top right quadrant (labelled I). If the impact of social cleavages on attitudes is similar across regions but varies on vote according to the social and political context (rational choice perspective), we might expect some of the data points to be in the bottom right quadrant of the graph (labelled II). Finally, if the impact of social cleavages on attitudes and vote varies in tandem according to the political context (the party identification model) we would expect to find data points in the bottom left quadrant of the graph (labelled III). [Figure 1 about here] 9 This model is a null hypothesis model. That is, it cannot validate the sociological approach, but it allows us to determine if regions deviate from the pattern implied by the sociological approach. Likewise, it does not disprove the party identification or rational choice models, but it can suggest support for them. [Figure 1 about here] RESULTS Tables 1 and 2 display the unadjusted coefficients for the models of attitudes regressed on social group variables. Notice that the residual standard error for each model is also reported so that the adjusted coefficients used in the scatterplots can be calculated. Tables 3 and 4 display the probit models fit to left and right vote respectively. A glance at the tables does indeed show that there are significant group differences in attitudes and voting in all regions. As said earlier, however, we confine our discussion to those variables related to our hypotheses. Figure 2 evaluates the hypothesis that, compared to the young, the old are more authoritarian and more likely to vote for right-wing parties. The adjusted coefficients representing the old (a dummy variable contrasting over 65 years of age with those under 30 years of age) from the models of libertarian-authoritarian attitudes are plotted along the horizontal axis. The corresponding coefficients from the probit models of left vote and right vote are plotted along the vertical axes. The lines through the data are lowess smooths of the trends in the relationships of the impact of social groups on attitudes and vote across regions (see Fox, 2000 for a good description of smoothing techniques). Figure 2 provides a very clear picture that, as predicted, age has a similar effect on attitudes in all regions—the young are more libertarian than the old. [Figure 2 about here] As expected, the old are also typically more likely to vote for right-wing parties, which is what was expected. The findings are somewhat surprising with respect to left vote, however. Quebec deviates significantly from the general pattern—in all other regions there is no significant effect, but old Quebecers are less likely to vote left. Here the party competition structure of the region plays a role. Although the New Democratic Party does exist in Quebec, it is a very minor player, with the left being dominated by the Bloc Quebecois, which is a strong nationalist party. Since the old are less likely to be nationalist in Quebec (Nadeau and Fleury, 1995), they avoid the Bloc Quebecois because of its nationalist rather than left-wing policies. Age also seems to have a stronger effect on vote in the east and west of Canada than in other regions, though the coefficients are statistically insignificant. We now turn to Figure 3 which allows us to examine the hypotheses that nonwhites are more likely than whites to hold left attitudes and to vote for left parties. Recall that Scotland is omitted from this analysis because it had too few non-white respondents. Also in all other non-US regions race is simply treated as non-white versus 10 white, while in the US regions the nonwhites are further divided into blacks and Hispanics. The coefficients in Figure 3 contrasts visible minorities with whites. Striking about this graph is how strongly related are the impact of race on attitudes and vote—i.e., the coefficients from the left-right attitudes and left and right vote models vary in tandem. Even more striking, however, are the significant regional differences within the USA, especially with respect to the contrasts between blacks and whites. The Democratic Party’s greater emphasis on the concerns of blacks is clearly reflected in higher support from blacks than experienced by the Republicans. Despite this, it is difficult to explain why the impact of being black versus white has a positive effect on authoritarian attitudes in the US south while it is a negative impact elsewhere. [Figure 3 about here] Figure 4 displays the coefficients contrasting the religiously devoted (those who attend religious services at least once a month) with the less religious. As expected, religiosity is positively associated with authoritarian attitudes in all regions—in no region is the coefficient negative. These attitudes are not always reflected in voting patterns, however, and two things are noteworthy. First, religiosity has its strongest impact on vote in the US regions. It seems sensible to suggest that this is largely due to the fact that the Republican Party has closer ties to the religious right than do the right-wing parties in Canada and Britain. Secondly, in Quebec—the region with the strongest nationalist movement—religiosity has a much stronger impact on vote than it does elsewhere. This finding has less to do with religiosity than the relationship between church (its quite possible that religiosity and religion are closely tied together) and party competition. The Reform Party is a non-factor in Quebec because of it’s perceived anti-Quebec sentiment. As a result, the much less socially conservative Progressive Conservative Party is the only choice for those on the right. The Liberal Party, on the other hand, has historically been the party of Quebec Catholics, and may benefit from the Reform Party’s lack of presence. Although Scotland and Northern Canada appear to differ from the general pattern of the data, the impact of religiosity on vote is statistically insignificant in both regions. [Figure 4 about here] Figure 5 allows us to test the hypothesis that social class affects left-right attitudes and vote similarly. We expect to find that unskilled manual labourers are more left in terms of attitudes and voting. Not surprisingly, considering previous research on class voting, we find significant support for this hypothesis in Britain (see Weakliem and Heath, 1999). Here the sociological model works perfectly well. We find little support for the hypothesis that class affects attitudes and voting in a similar manner in the regions of Canada and the USA, however. [Figure 5 about here] Ontario is exceptional compared to other North American regions in that the attitudes of the unskilled are significantly more left than those of managers, and these 11 attitudes are also reflected in a greater likelihood for working class people to vote left compared to managers. Ontario’s apparent greater level of class awareness may reflect the strength of the manufacturing sector and the strong connection between the labour unions in these sectors and the NDP. The situation is more striking in the US. Although unskilled workers are, on average, equally or more left than managers in all regions, they are not significantly more likely to vote left in any of the regions. Most interesting is the case of the northeast, where although the difference between unskilled workers and managers in terms of right voting is just as big as it is in any of the British regions, this is not reflected in a greater propensity to vote left. This seemingly disjointed finding probably reflects that a much higher proportion of unskilled labourers compared to managers abstain from voting in the US northeast. DISCUSSION This paper set out to integrate the major approaches to voting behaviour in one theoretical framework. We applied our theory to the major regions of Canada, Great Britain and the USA. Our analysis is unique in that it models attitudes and voting separately rather than includes attitudes as a predictor of vote. We argue that the conventional method ignores that attitudes are, at least partly, determined by social group membership. We were also unconventional in our analysis of the relative effects of many different social group variables. Political sociologists usually examine only one major social group (e.g., social class) without controlling for, or analysing the effects of, other major social groups. By including attitudes in models of vote one deflates the full effects of social group membership on voting, ignoring indirect effects through attitudes. By not controlling for other social group variables we cannot have confidence that the social group under analysis actually has the observed effect. Using a novel method we showed how the effects of social cleavages on vote and attitudes in different regions can be compared even when survey questions are not identical. Our results indicate that countries should not necessarily been treated as homogenous regions; that even in apparently similar regions there can be differences in group attitudes and voting. The results of our analyses suggest that the sociological explanation of voting behaviour holds most often when there are strong parties representing the interests of the relevant social groups. In particular, we found remarkable uniformity in the social basis of attitudes, with race being an obvious exception. Despite the near uniformity in the relationship between social groups and attitudes across regions, there were significant differences in voting patterns that seem to reflect differences in party structures. For example, the impact of social class on voting was highly variable despites very similar affects on attitudes. There are some limitations to the study, most of which are related to the data employed. The data were not collected with the intent of being divided into many regions, meaning that the samples sizes employed here were somewhat smaller than ideal. Moreover, some of our regions could have been further divided had the data permitted it. For example, party competition is quite different in British Columbia and Alberta, but because of small numbers we group together these provinces in the West of 12 Canada. Larger samples sizes would allow greater confidence in our estimates, making it practical to plot confidence regions around them in the scatterplots. (For the present data, confidence regions are large enough that inclusion of them in the scatterplots would muddle the picture). Despite this limitation, we find significant differences between regions within countries. This point cries out for further research and the collection of new data for this purpose. Further research could also address other attitude dimensions not tackled in this paper. With the intensification of global trade and nationalist movements, national sentiment is an increasingly important attitudinal dimension to consider. Research has shown that British national sentiment cannot be reduced to the left-right and libertarian attitude dimensions, but is related to attitudes towards European integration and Scottish and Welsh devolution (Heath et al 1999, Heath and Kellas, 1998). Heath et al (1999) conclude that, although not as important as left-right attitudes, national sentiment plays as strong a role as libertarian attitudes in voting behaviour in Britain. No similar work has been done in Canada and the US, however, and we did not have appropriate questions to be able to measure the concept of national sentiment for either country. Even more obvious, national identity would have a strong impact on voting in Quebec, Scotland and Wales, where there are independent parties representing national interests. Despite that we examined 14 regions, that we had only three countries also limits the scope of our findings. 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The CES data were not designed with the specific purpose of creating these indices but they do include a large number of appropriate questions. Our initial strategy was to limit the number of items to be used through exploratory factor analysis. Once the number of items was reduced, we created additive scales similar to those employed from the BES data. All scales have good internal consistency as shown by the Cronbach’s alpha (British libertarian-authoritarian scale a=.590; British left-right scale a=.667; Canadian libertarian-authoritarian scale a=.563; Canadian left-right scale a=.655; American libertarian-authoritarian scale=.637; American left-right scale=.743). The items used for each of the scales are listed below. BES Left-right scale9 1. Ordinary people get their fair share of the nation’s wealth 2. There is one law for the rich and one for the poor 3. There is no need for strong trade unions to protect employee’s working conditions and wages 4. Private enterprise is the best way to solve Britain’s economic problems 5. Major public services and industries ought to be in state ownership 6. It is the government’s responsibility to provide a job for everyone who wants one BES Libertarian-Authoritarian Scale 1. Young people today don’t have enough respect for traditional British attitudes 2. Censorship of films and magazines is necessary to uphold moral standards 3. People should be allowed to organise public meetings to protest against government 4. Homosexual relations are always wrong 5. People in Britain should be more tolerant of those who lead unconventional lives 6. Political parties which wish to overthrow democracy should be allowed to stand in general elections CES Left-Right scale 10 1. There's not much ANY government can do these days to solve the unemployment problem 9 All of the items used in both BES scales are Likert items with the following response format: “agree strongly”, “agree”, neither agree nor disagree”, “disagree” or “disagree strongly”. Both scales are also balanced so that there are equal numbers of questions worded in favour of both directions of the scales, limiting response-set bias. 10 The questions used from the CES to construct the Left-Right scale did not all have similar response formats. The first four questions used five point Likert scales with the following responses: “agree strongly”, “agree”, neither agree nor disagree”, “disagree” or “disagree strongly”. As can be seen from the wording of the questions, the response format for questions 4 thru 9 was the following: “a lot”, “some”, not at all” “not at all”. Don’t know responses were coded so that they were situated between “some” and “not at all”. 18 2. 3. 4. 5. 6. 7. 8. To maintain our social programmes we must eliminate the deficit The government should leave it ENTIRELY to the private sector to create jobs When businesses make a lot of money, everyone benefits, including the poor Would you cut WELFARE spending A LOT, SOME, or NOT AT ALL? Would you cut PENSIONS A LOT, SOME, or NOT AT ALL? Would you cut HEALTH CARE A LOT, SOME, or NOT AT ALL? Would you cut UNEMPLOYMENT INSURANCE A LOT, SOME, or NOT AT ALL? 9. Would you cut EDUCATION A LOT, SOME, or NOT AT ALL? CES Libertarian-Authoritarian Scale11 1. 2. 3. 4. 5. 6. Only people who are married should be having children Society would be better off if more women stayed home with their children. How do you feel about Aboriginal peoples? How do you feel about people on welfare? How do you feel about gays and lesbians? How do you feel about racial minorities ANES Left-Right Scale12 1. If people were treated more equally in this country we would have many fewer problems. 2. Our society should do whatever is necessary to make sure that everyone has an equal opportunity to succeed. 3. One of the big problems in this country is that we don't give everyone an equal chance. 4. ONE, the less government, the better; or TWO, there are more things that government should be doing? 5. ONE, we need a strong government to handle today's complex economic problems; or TWO, the free market can handle these problems without government being involved. 6. ONE, the main reason government has become bigger over the years is because it has gotten involved in things that people should do for themselves; or TWO, government has become bigger because the problems we face have become bigger. 11 As with the Left-Right scale, the questions used from the CES to construct the Libertarian-Authoritarian scale did not all have similar response formats. The first two questions used five point Likert scales with the following responses: “agree strongly”, “agree”, neither agree nor disagree”, “disagree” or “disagree strongly”. For questions 3 thru 6 respondents were asked to give a score on a 0 to 100 scale, where 0 means they “really dislike” the group and 100 means they “really like” the group. In order to make them similar to the Likert questions so that they could be added together, these responses to these questions were collapsed into 5 categories. For the most part this had little effect on the response distributions of the variables since the data were essentially in five clusters. 12 The first three questions used five point Likert scales with the following responses: “agree strongly”, “agree”, neither agree nor disagree”, “disagree” or “disagree strongly”. Questions 4 thru 6 respondents had three category responses, with a middle option accepted when declared. 19 ANES Libertarian-Authoritarian Scale13 1. The newer lifestyles are contributing to the breakdown of our society. 2. This country would have many fewer problems if there were more emphasis on traditional family ties 3. Mothers should remain at home with young children and not work. 4. The world is always changing and we should adjust our view of moral behavior to those changes. 5. Do you feel STRONGLY or NOT STRONGLY that homosexuals should (or should not) be allowed to serve in the United States Armed Forces? 6. Do you favor (or oppose) laws to protect homosexuals against job discrimination STRONGLY or NOT STRONGLY? 13 Each of the six questions used for the ANES libertarian-authoritarian scale were Likert-type items with five response categories. 20 Table 1. Ordinary Least Squares regression of left-right attitudes on social group variables (standard errors in parentheses) Canada Great Britain Explanatory West Ontario Quebec East North South Mid. Variable England England Men 2.154** 1.639** 1.751** .854 1.008 .419 .015 (.446) (.538) (.460) (.671) (1.137) (.259) (.288) Age (reference=18-29) 65 + 1.779* 2.189* 1.697 .248 -1.687 .396 .842 (.919) (1.121) (.959) (1.517) (3.524) (.453) (.485) 46-64 1.232 1.127 .013 -2.058 -1.013 -.275 .682 (.730) (.864) (.693) (1.057) (2.120) (.408) (.422) 30-45 .927 1.087 .341 -.599 -.692 -.352 -.447 (.705) (.798) (.628) (.989) (1.928) (.390) (.394) Race (reference=white) Black 1.939* 1.550 -.162 -4.250* -1.870 1.236* .607 (.882) (.900) (.861) (2.076) (1.550) (.594) (.810) Hispanic __ __ __ __ __ __ __ Religious Education (reference=low education) University Some post-secondary A-level High School/ O-level or CSE Social Class (reference=managers) Professionals Self-employed Clerical Skilled manual Semi- or unskilled manual Unclassified Constant Residual standard error R2 N *p-value<.05 **p-value<.01 North England -.203 (.351) Scotland Wales .434 (.299) .445 (.255) .813 (.589) .288 (.506) -.626 (.489) .680 (.477) -.175 (.416) -.254 (.402) -1.490 (.988) __ __ United States West North-east South .243 (2.555) North Central -1.482 (1.868) .657 (2.017) 1.170 (1.754) 1.231** (.423) -.274 (.382) .226 (.368) -.624 (.887) -.144 (.795) .505 (.762) .526 (.767) .457 (.714) .957 (.700) 1.874 (1.031) 1.679 (.921) 1.698 (.878) 1.269* (.573) 1.078* (.512) .437 (.491) __ -.738* (.314) __ -3.445** (1.280) -3.210** (.950) .333 (.251) -5.509** (1.201) -.685 (1.142) .495* (.214) -3.790** (.803) -.006 (1.164) -.113 (.273) 3.252** (.628) 1.960** (.544) 1.265* (.513) .201 (.237) .138 (.277) .610* (.287) -.219 (.329) .851 (.696) .165 (.151) .196 (.175) -.042 (.208) .116 (.158) .060 (.148) -.451 (.703) .785 (.644) __ .355 (.825) .152 (.782) __ -.890 (.743) -.302 (.674) __ .750 (1.046) .572 (.929) __ 1.202 (1.691) .911 (1.656) __ 1.540 (1.857) .756 (.450) .712 (.382) .540 (.474) 1.044** (.300) 3.252** (.628) 1.960** (.544) __ -.564 (.954) 1.683** (.562) .058 (.470) -.436 (.420) .253 (.359) .770 (1.018) .002 (.951) __ .193 (.708) .022 (.616) .335 (.567) .782 (.599) .121 (.405) 1.190 (.869) .552 (.763) __ .233 (.778) -.044 (.590) .017 (.477) .298 (.497) -.210 (.354) 1.747 (1.179) 1.474 (1.125) __ .728 (.670) .733 (.453) 1.014 (.327) 1.030* (.456) 1.343** (.327) .742 (1.081) .795 (.693) -.575 (.924) 1.265* (.513) -.365 (.989) -.224 (.993) -.592 (1.291) -2.009 (1.159) .581 (.955) -1.544 (.999) 19.81** 6.27 .052 890 -.983 (1.137) .012 (1.230) -1.858 (1.431) -2.277 (1.438) -.445 (1.141) -.508 (1.163) 20.68** 6.11 .050 596 .501 (.975) 1.939 (1.067) .909 (1.154) .054 (1.271) .148 (.942) .171 (.942) 20.85** 5.81 .052 681 -2.408 (1.398) 1.556 (1.529) -4.583** (1.769) -1.509 (1.633) -1.668 (1.317) -1.556 (1.402) 21.21** 5.28 .099 290 -.913 (1.924) 1.084 (1.961) -1.598 (2.756) 2.659 (2.599) .308 (2.129) .497 (2.032) 19.88** 5.63 .067 117 -1.046** (.371) -.357 (.509) -1.037 (.401) -2.527** (.437) -1.293** (.419) .229 (.920) 15.12** 3.64 .075 976 -1.422** (.478) -.444 (.654) -.736 (.498) -2.144** (.517) -1.974** (.485) -.017 (.712) 16.28** 3.14 .089 595 -1.051* (.533) -1.064 (.885) -2.002** (.569) -2.654** (.555) -2.430** (.540) -.001 (.999) 18.08** 3.68 .092 611 -.622 (.495) .003 (.821) -1.310* (.514) -2.702** (.523) -2.484** (.489) -.363 (.738) 15.67** 3.57 .123 752 -.967 (.536) -.969 (.525) -1.463** (.379) -1.532** (.439) -1.861** (.399) -.548 (.497) 15.98** 3.51 .073 1040 -2.039* (.867) -.396 (1.041) -1.741 (.903) -1.818* (.865) -3.167** (1.319) -2.763** (.972) 13.72** 4.19 .140 312 -.027 (.844) 2.024* (.937) -.408 (.777) .333 (.770) .255 (.866) .054 (.900) 12.15** 4.09 .102 415 -.807 (.930) -.024 (1.135) -1.919 (.993) -1.222 (.964) -2.561* (1.138) -.662 (1.032) 12.29** 3.83 .206 233 -1.207 (.619) -.013 (.768) -.645 (.677) -.133 (.654) -.853 (.699) -.877 (.720) 11.16** 3.83 .224 572 Table 2. Ordinary Least Squares regression of libertarian-authoritarian attitudes on social group variables (standard errors in parentheses) Canada Great Britain Explanatory West Ontario Quebec East North South Mid. North Variable England England England Men 1.075** .719 .867** .100 .448 .222 -.352 .566 (.323) (.393) (.290) (.552) (.832) (.217) (.282) (.280) Age (reference=18-29) 65 + 3.749** 3.663** 3.216** 2.442* 2.491 2.500** 3.085** 3.572** (.665) (.818) (.603) (1.247) (2.579) (.380) (.473) (.472) 46-65 2.591** 1.869** 1.688** 2.214 2.895 1.887** 2.508** 2.292** (.528) (.630) (.436) (.868) (1.551) (.342) (.411) (.405) 30-45 1.712** 1.317* .652 1.308 1.956 .647* 1.377** 1.029** (.510) (.582) (.395) (.813) (1.410) (.328) (.384) (.392) Race (reference=white) Black .228 1.418* -.626 -2.698 -.353 -.564 -1.264 -.045 (.638) (.657) (.541) (1.706) (1.131) (.497) (.791) (.791) Hispanic __ __ __ __ __ __ __ __ Religious Education (reference=low education) University Some post-secondary A-level High School/ O-level or CSE Social Class (reference=managers) Professionals Self-employed Clerical Skilled manual Semi- or unskilled manual Unclassified Constant Residual standard error R2 N *p-value<.05 **p-value<.01 Scotland Wales -.252 (.253) .512* (.205) 2.579** (.404) 1.741** (.352) .435 (.340) __ United States West North-east South 3.439 (2.703) North Central -4.787* (1.947) -3.921 (2.365) 3.117 (2.088) 3.419** (.341) 2.514** (.308) 1.250** (.296) 4.370** (.938) 3.557** (.842) 2.745** (.806) 2.202** (.799) 1.679* (.744) 1.381 (.729) 3.290** (1.208) 1.848 (1.080) .969 (1.030) 3.740** (.682) 2.410** (.613) 2.075** (.584) __ .767** (.253) __ -3.061* (1.354) -1.173 (1.005) 1.797** (.265) -2.868* (1.256) -1.146 (1.190) 1.358** (.223) .654 (.942) -.010 (1.365) .527 (.320) -2.397** (.514) -.877 (.755) .988** (.197) .927** (.172) .800** (.202) .519** (.181) .603** (.271) 1.600** (.509) .845** (.127) .749** (.171) .393* (.167) .599** (.134) .342** (.119) -2.900** (.509) -1.743** (.467) __ -2.964** (.601) -2.114** (.570) __ -2.847** (.467) -1.522** (.424) __ -3.578** (.860) -2.090** (.764) __ -1.135 (1.238) 1.305 (1.211) __ -.192 (1.359) -1.003** (.353) -.348 (.307) -.657 (.382) .269 (.242) -.635 (.747) .433 (.648) __ -1.311 (.784) -1.532** (.476) -.773 (.397) -1.238** (.355) -.095 (.304) -1.855 (1.193) -1.666 (1.115) __ -1.009* (.445) -3.102** (.493) -.235 (.454) -.846 (.479) -.372 (.324) -.827 (.906) -.146 (.795) __ -.648 (.568) -2.661** (.576) -.500 (.465) -.751 (.489) .355 (.342) -1.882 (1.247) -1.253 (1.190) __ -1.009* (.485) -2.548** (.379) -.667* (.324) -1.177** (.383) -.158 (.274) -1.136 (1.143) -.508 (.723) -1.031 (1.083) .091 (.611) -.340 (.716) .764 (.718) .795 (.718) .880 (.839) .039 (.691) -.456 (.723) 17.03** 4.53 .157 890 -1.221 (.829) -.677 (.897) -1.847 (1.043) .144 (1.048) -.218 (.832) -1.036 (.848) 17.84** 4.57 .176 596 .668 (.613) 1.767 (.671) 1.234 (.725) 1.687 (.799) .980 (.592) .771 (.592) 16.30** 3.65 .205 681 .867 (1.149) 1.870 (1.256) .508 (1.454) 1.061 (1.341) 1.581 (1.082) 1.800 (1.152) 16.45** 4.34 .219 290 -1.380 (1.408) -.588 (1.435) .320 (2.017) 3.719 (1.902) .604 (1.558) .946 (1.487) 14.48** 4.12 .302 117 -.267 (.311) .847* (.427) .370 (.335) .310 (.366) .505 (.351) .130 (.771) 18.86** 3.05 .234 976 -.903 (.466) -.025 (.632) .918 (.486) .324 (.504) -.193 (.473) -.608 (.695) 19.55** 3.06 .256 595 -.558 (.426) -.551 (.709) -.278 (.456) -.025 (.445) -.180 (.432) .285 (.800) 17.95** 2.95 .262 611 -.442 (.419) -.008 (.435) .539 (.695) -.092 (.443) -.521 (.414) -1.106 (.625) 18.57** 3.02 .187 752 -.096 (.432) .601 (.422) .016 (.305) .761* (.354) .447 (.322) .025 (.401) 16.44** 2.83 .201 1040 -.783 (.917) -.225 (1.100) -1.111 (.955) -.978 (.915) -1.149 (1.395) .671 (1.029) 17.48** 4.44 .259 312 -.614 (.880) 2.608** (.976) .287 (.810) 1.205 (.803) 1.447 (.902) 3.024 (.939) 18.09** 4.27 .172 415 -.427 (1.090) 1.248 (1.331) 1.240 (1.165) -.786 (1.131) .343 (1.335) .342 (1.210) 18.21** 4.49 .134 233 .558 (.737) 2.047* (.914) .999 (.805) 1.645* (.779) 1.615 (.833) 1.276 (.857) 18.81** 4.56 .156 572 1 Table 3. Probit models of left vote regressed on social group variables (standard errors in parentheses) Canada Great Britain Explanatory West Ontario Quebec East North South Variable England Men -.482** -.429** .131 -.152 -.525 .030 (.119) (.159) (.217) (.188) (.349) (.098) Age (reference=18-29) 65 + -.324 .165 -.405 -.391 1.303 .076 (.234) (.309) (.529) (.452) (.979) (.175) 46-64 -.310 .145 -.208 .110 .530 .264 (.183) (.241) (.350) (.280) (.670) (.151) 30-45 -.195 -.095 .239 .101 -.089 0.067 (.173) (.228) (.276) (.262) (.631) (.058) Race (reference=white) Black -.187 -.253 .181 .591 -.464 -1.191** (.243) (.277) (.357) (.512) (.588) (.221) Hispanic __ __ __ __ __ __ Religious Education (reference=low education) University Some post-secondary A-level High School/ O-level or CSE Social Class (reference=managers) Professionals Self-employed Clerical Skilled manual Semi- or unskilled manual Unclassified Constant X 2 Model Improvement df N *p-value<.05 **p-value<.01 Mid. England -.062 (.119) North England .006 (.120) Scotland Wales -.006 (.108) -.069 (.092) .262 (.205) .336 (.178) .511* (.166) .038 (.204) .254 (.176) .302 (.170) -.054 (.172) .012 (.150) .142 (.144) -.941** (.346) __ -.593 (.347) __ __ United States West North-east South -2.989 (3.109) North Central -2.356 (2.396) .145 (.663) .267 (.591) .133 (.153) .336* (.139) .234 (.135) .385 (.275) .383 (.248) .246 (.239) .222 (.244) .143 (.229) -.383 (.228) .404 (.346) .247 (.310) .296 (.297) .474 (.198) .276 (.180) .253 (.173) __ -.011 (.114) __ .712 (.403) -.017 (.297) -.058 (.076) 1.240** (.386) .122 (.370) -.157* (.069) .785 (.281) .183 (.386) -.057 (.091) .758** (.146) .296 (.213) .026 (.056) -.179** (.065) -.124 (.081) -.022 (.154) -.174 (.091) -.232 (.212) -.067 (.058) -.102 (.073) .037 (.072) -.015 (.057) -.087 (.053) .142 (.184) -.090 (.174) __ .588* (.244) .417 (.237) __ .991** (.439) .496 (.438) __ .166 (.295) .067 (.267) __ 1.297* (.605) .817 (.609) __ .838 (.666) -.082 (.162) -.096 (.138) -.244 (.171) -.551** (.109) .065 (.212) -.202 (.185) __ .354 (.261) -.285 (.209) -.293 (.172) -.018 (.149) -.064 (.128) -.024 (.339) .284 (.318) __ .312 (.486) -.081 (.213) -.282 (.197) -.180 (.207) .043 (.139) .198 (.287) .193 (.253) __ .128 (.249) .414 (.242) .055 (.197) -.031 (.208) -.033 (.147) -.182 (.367) .092 (.350) __ -.087 (.183) -.080 (.167) -.645** (.154) -.294 (.171) -.277* (.120) -.134 (.335) .313 (.229) -.080 (.307) -.254 (.174) .496 (.272) .175 (.287) .152 (.355) .527 (.318) .166 (.273) .322 (.279) -1.054** 35.51 15 890 .473 (.370) .464 (.400) .674 (.428) .322 (.485) .355 (.381) .534 (.379) -1.921** 25.41 15 596 .024 (.395) -2.190 (3.731) .231 (.482) -2.209 (4.969) .139 (.416) .324 (.404) -2.170** 20.65 15 681 .087 (.373) .471 (.396) .363 (.458) -.093 (.450) -.007 (.354) -.009 (.381) -1.043* 19.52 15 290 .828 (.551) .064 (.592) .738 (.753) -2.208 (4.382) -.300 (.743) .312 (.593) -2.021** 25.13 15 117 .299* (.146) .388* (.191) .367* (.157) .491** (.166) .427** (.160) -1.005 (.528) .229 81.33 16 976 .318 (.199) .120 (.276) .142 (.210) .546 (.216) .466 (.203) -.043 (.317) -.090 34.97 16 595 -.120 (.183) -.865** (.335) -.030 (.195) .223 (.190) .098 (.185) -.300 (.353) .362 25.40 16 611 -.041 (.186) .236 (.295) .199 (.188) .531 (.190) .500 (.179) .413 (.264) -.469 40.65 15 752 .109 (.193) .246 (.189) .245 (.137) .543** (.161) .481** (.145) .236 (.180) -.250 65.52 16 1040 .001 (.261) -.316 (.276) -.124 (.317) -.151 (.262) -.486 (.411) -.454 (.300) -.291 15.43 16 312 .856** (.275) .204 (.311) .294 (.256) .259 (.251) -.117 (.285) -.223 (.303) -.792* 42.33 16 415 .337 (.311) -.104 (.381) .165 (.331) .127 (.323) .024 (.382) -.126 (.345) -.571 18.08 16 233 -.094 (.206) -.385 (.267) -.268 (.230) -.195 (.221) -.109 (.237) -.466 (.247) -.474 45.48 16 572 2 Table 4. Probit models of right vote regressed on social group variables (standard errors in parentheses) Canada Great Britain Explanatory West Ontario Quebec East North South Variable England Men -.165 .206 .114 .383* -.285 -.072 (.122) (.137) (.111) (.171) (.322) (.096) Age (reference=18-29) 65 + .315 -.139 .550* -.169 1.329 .293 (.269) (.271) (.249) (.378) (.102) (.170) 46-64 .467* -.194 .344 -.550* .661 .212 (.223) (.215) (.181) (.267) (.650) (.154) 30-45 .254 -.201 .132 -.434 .205 -.051 (.222) (.200) (.167) (.246) (.620) (.151) Race (reference=white) Black -.347 -.171 .003 .332 -.526 .774** (.290) (.238) (.227) (.501) (.553) (.274) Hispanic __ __ __ __ __ __ Religious Education (reference=low education) University Some post-secondary A-level High School/ O-level or CSE Social Class (reference=managers) Professionals Self-employed Clerical Skilled manual Semi- or unskilled manual Unclassified Constant X 2 Model Improvement df N *p-value<.05 **p-value<.01 Mid. England -.204 (.131) North England -.149 (.143) Scotland Wales -.014 (.151) .049 (.114) .730** (.223) .579** (.198) .205 (.192) .910 (.259) .601 (.233) .120 (.236) 1.304** (.284) .842** (.266) .446 (.268) .751 (.505) __ -.082 (.430) __ __ United States West North-east South .666 (.928) North Central .466 (.665) .381 (.770) .899 (.651) .862** (.204) .705** (.188) .290 (.186) 1.130** (.337) .866** (.315) .816** (.307) .591 (.278) .368 (.260) .480 (.257) .770 (.447) .452 (.416) .456 (.400) .557* (.235) .397 (.209) .159 (.204) __ -.296 (.155) __ -3.591 (3.582) -.367 (.324) .224** (.081) -3.334 (2.194) -.454 (.421) .346** (.073|) -1.214* (.497) -.361 (.483) .306** (.110) -3.498* (1.750) -.322 (.257) .247** (.067) .066 (.063) .098 (.069) -.221** (.078) .071 (.084) -.256 (.211) .111** (.055) .066 (.076) .042 (.079) -.073 (.078) .173** (.060) .506** (.206) .440* (.195) __ .396 (.213) .359 (.205) __ -.214 (.189) -.134 (.170) __ -.279 (.263) -.562 (.239) __ .145 (.475) -.185 (.493) __ .244 (.525) .422* (.192) .162 (.172) .758** (.205) .621** (.134) 1.974** (.353) 1.694** (.331) __ -.237 (.238) .382 (.248) .074 (.233) .160 (.222) .211 (.190) .534 (.418) .268 (.410) __ -.076 (.178) .103 (.236) .128 (.227) .457 (.239) -.092 (.176) 1.147** (.318) .781** (.288) __ .173 (.209) -.227 (.280) .210 (.208) .351 (.221) .222 (.158) .722 (.415) .526 (.395) __ .446* (.200) -.272 (.173) .256 (.141) .085 (.172) .235 (.121) .348 (.385) .434 (.272) .555 (.409) 1.282** (.323) -.222 (.249) -.365 (.259) -.329 (.341) -.410 (.327) -.299 (.245) -.101 (.250) -1.633** 22.53 15 890 -.091 (.289) .190 (.303) .107 (.357) -.093 (.366) -.248 (.299) .181 (.290) -1.205** 17.68 15 596 -.362 (.237) -.204 (.254) -.110 (.275) -.226 (.306) -.313 (.227) -.514* (.231) -.881** 20.81 15 681 -.033 (.367) -.270 (.404) .394 (.451) -.026 (.423) .104 (.340) .057 (.364) -.097 18.76 15 290 -.351 (.509) -.678 (.544) -.630 (.760) -.333 (.738) -.352 (.568) -.791 (.581) -.931 9.01 15 117 -.138 (.135) -.182 (.144) .048 (.181) -.678** (.171) -.463** (.157) -.158 (.343) -1.196** 66.92 16 976 -.565** (.203) -.675* (.287) -.474* (.210) -.732** (.226) -.764** (.210) -.606 (.325) -1.269* 48.11 16 595 -.208 (.197) -.118 (.339) -.363 (.218) -.811** (.237) -.742** (.220) -.480 (.416) -.830 62.10 16 611 .157 (.210) -.100 (.231) .132 (.343) -.897** (.286) -.897** (.260) -.190 (.354) -1.889** 77.11 15 752 -.293 (.229) -131 (.151) -.334 (.225) -.432* (.189) -.489** (.170) -.557 (.227) -1.444** 94.18 16 1040 .143 (.286) .410 (.345) .119 (.310) .277 (.290) .352 (.457) .267 (.326) -1.986** 36.29 16 312 -.536 (.281) .198 (.305) -.331 (.261) -.170 (.259) -.321 (.312) -.195 (.308) -1.388** 78.24 16 415 .071 (.333) -.234 (.377) .069 (.396) -.855* (.413) -1.148* (.582) -.030 (.375) -1.332** 43.19 16 233 -.041 (.216) .101 (.275) -.304 (.267) .197 (.244) .151 (.283) .066 (.290) -2.298** 166.98 16 572 3 Figure 1 Graph showing the expected relationships between the adjusted coefficients from OLS regression models of attitudes and coefficients from probit models of vote for the three models of voting behaviour. The sociological explanation is plausible when the data are in quadrant I (i.e, social group affects both attitudes and voting in the same manner) . Data in quadrant II support the rational choice model (i.e., social group affects attitudes in one way, but voting does not reflect attitudes). Support for the party identification model (i.e., when attitudes do not reflect social group interests, but voting reflects attitudes) is found when the data are in quadrant III. 1.0 Vote coefficient .5 0.0 -.5 -1.0 -1.0 -.5 0.0 .5 Attitides coefficient 4 1.0 Figure 2. Old versus young 2.0 cano Left vote 1.0 usne usnc usso caon gbse gbsc 0.0 uswe gbme Country United States cawe caqu caea Great Britain Canada -1.0 .4 .8 1.2 Libertarian-authoritarian attitudes Figure 2. Old versus young 2.0 cano gbsc uswe 1.0 Right vote usne usnc gbme usso caqu cawe gbse Country 0.0 caea caon United States Great Britain Canada -1.0 .4 .8 1.2 Libertarian-authoritarian attitudes 5 Figure 3. Nonwhites versus whites 2.0 usnc_b usne_b usw_b caea usso_b caqu usne_h usnc_h gbwa usw_h 0.0 Left vote cano gbne usso_h cawe caon gbme gbse Country -2.0 United States Great Britain Canada Total Population -4.0 -1.5 -1.0 -.5 0.0 .5 1.0 1.5 Left-right attitudes Figure 3. Nonwhites versus whites 2 gbmegbse caea caqu caon gbwausne_h caweusso_h usnc_h cano gbne 0 Right vote usw_h usne_b Country -2 United States Great Britain usnc_b usso_b usw_b Canada Total Population -4 -1.5 -1.0 -.5 0.0 .5 1.0 Left-right attitudes 6 1.5 Figure 4. Religious versus less religious .5 .4 .3 Left vote .2 .1 gbne caqu usne gbwa .0 -.1 usso gbsc gbme caon caea uswe gbse Country usnc cawe cano -.2 United States -.3 Great Britain -.4 Canada -.5 0.0 .1 .2 .3 .4 .5 Libertarian-authoritarian scale Figure 4. Religious versus less religious .5 .4 usnc usne .3 Right vote .2 usso uswe gbwa caea gbne .1 .0 caon gbse cawe gbme gbsc Country -.1 caqu -.2 United States cano -.3 Great Britain -.4 Canada -.5 0.0 .1 .2 .3 .4 Libertarian/authoritarian scale 7 .5 Figure 5. Unskilled labour versus managers .8 gbsc gbme gbwa gbse caon .4 caqu cawe Left vote gbne usne caea -.0 usso usnc cano Country -.4 uswe United States -.8 Great Britain Canada -1.2 -.8 -.6 -.4 -.2 0.0 .2 Left-right attitudes Figure 5. Unskilled labour versus managers .8 .4 uswe Right vote caea usso -.0 caon gbwa -.4 cawe caqu usnc cano gbse Country United States gbne gbme -.8 gbsc Great Britain Canada usne -1.2 -.8 -.6 -.4 -.2 .0 Left-right attitudes 8 .2