Ethnicity, Citizenship and Political Participation in Britain

By

Eldin Fahmy

ESRC/ODPM Postgraduate Research Programme

Working Paper 14

2005 ISBN: 1-903825-24-5

Preface

This Working Paper is the third to be produced from the Citizenship and Attitudes to Governance in Britain project funded jointly by the Economic and Social Research Council and the Office of the Deputy Prime Minister as part of the ODPM’s Sustainable Communities Postgraduate Research Programme. Using a broad range of survey sources this research project: Explores the extent and dynamics of social, community and political participation in Britain;

Considers evidence of declining levels of civic engagement in contemporary Britain; and

Examines the ways in which patterns of participation reflect underlying social and demographic differences, social networks and capital, and spatial effects using a range of cross-sectional data sources. Relevant data sources include: the British Household Panel Survey; the British Election Panel Survey; the 2001 Home Office Citizenship Survey; the 2001 Citizens’ Audit; the British Social Attitudes Survey. For further details see: http://www.bris.ac.uk/sps/ESRC-ODPM/welcome.htm Ade Kearns Programme Director a.j.kearns@socsci.gla.ac.uk

Abstract

The emergence of new political identities centred upon ethnic, religious and

cultural affiliations raises important questions about the changing nature of

political citizenship and civic engagement for Britain’s minority ethnic population.

Drawing upon data from the 2001 Home Office Citizenship Survey, this paper

explores the extent and nature of civic engagement and political participation

across ethnic groups in contemporary Britain. Important differences across ethnic

groups are identified in relation to the influence of social class, ethnic identity, and

residential ethnic mix as predictors of participation.

Contents I: Introduction .................................................................................................................... 1

II: Understanding Minority Civic Engagement........................................................... 3

III: Data, Hypotheses and Operationalisation............................................................. 6

IV: Testing the Alternative Models .............................................................................. 12

V: Presentation of Findings ............................................................................................ 13

VI: Interpretation of Findings........................................................................................ 21

Appendix............................................................................................................................ 23

References .......................................................................................................................... 25

I: Introduction The increasingly multicultural character of British society constitutes one of the key challenges for policy makers across a broad range of contemporary social and public policy arenas. The emergence of increasingly differentiated political identities centred upon ethnic, religious and cultural affiliations raises new questions about the changing nature of political citizenship and civic engagement for Britain’s growing minority ethnic population. In the wake of recent disturbances and ongoing inter-ethnic tensions consideration of issues relating to ‘race’, ethnicity and cultural identity clearly remain central to effective policies focused upon fostering active citizenship, civic engagement and community cohesion. At the same time, and despite the increasingly multicultural context of politics, racial discrimination and other, structural barriers to the effective exercise of political citizenship rights by minority ethnic populations constitute a fundamental challenge to the development of a genuinely inclusive and participatory political culture. This paper draws upon secondary analysis of survey data generated by the 2001 Home Office Citizenship Survey in order to explore the extent and nature of civic engagement and political participation across ethnic groups in contemporary Britain. Large scale studies of citizen participation in politics both within the UK and internationally repeatedly demonstrate the salience of ‘race’ as a determinant of political involvement and action (e.g. Saggar, 1998a; Parry et al., 1992; Verba & Nie, 1972). Existing research evidence on the relationship between ethnic identity and citizens’ political participation has been limited for a number of reasons. Firstly, in the UK context limited sample sizes have typically meant that the ethnic dimension of participation in politics has received comparatively little attention because sample estimates cannot be reliably generalised to the broader population (Catt, 1996). As a result, studies of the relationship between ethnicity and citizens’ politics have tended to focus exclusively upon the political attitudes and behaviour of ethnic minority groups based upon small-scale samples of specific minority populations (e.g. Saggar, 1998; Anwar, 1986, 1994). The emphasis has therefore been upon the ethnicity of particular ethnic minorities, with much less consideration accorded to the investigation of the general impact of ethnic and racial identities and cultural heritage upon patterns of citizens’ political engagement per se (Saggar, 2000). However, the implicit assumption that ethnic identity is not a salient dimension of citizens’ political identities for the white majority population has not been systematically investigated. Secondly, and partly as a consequence of the shortcomings of existing sample surveys, most studies have focused almost exclusively upon ethnic minority engagement with the electoral process, and the elite representation of minority

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groups within existing political institutions such as local government, parliament, and the political parties (e.g. Ali & O’Cinneide, 2002; Electoral Commission, 2002; Anwar, 2001, 1986; Le Lohé, 1998; Saggar, 1992). Whilst these are clearly agendas of crucial significance, it is also clear that citizen politics is about much more than voting. Indeed, as is often the case with politically marginalised groups, the emphasis upon formal participation through the ballot box can obscure the extent of broader forms of civic engagement by ethnic minority groups as expressed, for example, through community involvement, volunteering, political protest, as well as more diffuse forms of cultural contestation. Finally, although the political attitudes and action of minority ethnic populations has received considerable attention in empirical studies, the nature of this relationship remains under-theorised. As Saggar (1998b) argues, our understanding of what it is about ethnicity that counts in shaping political outlooks, identities and action remains under-developed. Ethnicity thus represents “an amalgam of contributory factors…selectively symbolising and uniting aspects of shared experience and common outlook” (p.12). Conventional accounts of political participation usually begin by examining the impact of ‘baseline’ social and demographic characteristics upon levels of political engagement. However, the exact mechanisms linking such factors with observed patterns of political engagement are not well specified within standard, ‘base-line models’. A central objective in the study of ethnic minority civic engagement should, therefore, be advancing understanding of how and why race and ethnicity influence citizens’ political attitudes and behaviour. This paper examines the validity of four competing theories held to explain inter-ethnic variance in citizens’ political attitudes and behaviour: Socio-Economic Status (SES); Social Capital; Psycho-Political Orientations, and; Ethnic Identity and Group Cohesion. Although each of these theories has been extensively applied in existing research, they have yet to be tested simultaneously in the study of inter-ethnic variations in political participation. However, a consideration of the validity of each of these approaches should advance understanding of the ways in which ethnic origin may help to ‘explain’ variations in political attitudes and behaviour.

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II: Understanding Minority Civic Engagement

Socio-Economic Status As noted above, conventional accounts of participation usually begin by examining the impact of observed social and demographic differences upon patterns of participation and political involvement. Underlying this approach is a concern with the effects of variations in individual resources upon political response. Virtually without exception empirical studies have demonstrated a positive relationship between measures of socio-economic status (e.g. income, education, social class) and political involvement, trust, efficacy, and participation, with higher status respondents reporting higher levels of political interest, knowledge, efficacy and participation in comparison with low status respondents (e.g. Dalton, 1996; Parry et al., 1992; Marsh, 1990; Barnes & Kaase, 1979; Verba et al., 1972). However, although this is an effective strategy in purely statistical terms with regard to measures of model fit, the analytic purchase of this approach remains uncertain. For example, it is unclear in what sense social class position acts as an individual ‘resource’ which facilitates participation. More generally, little progress has been made to date in specifying how ‘baseline’ socio-economic factors affect levels of political engagement. Despite the evident statistical power of this approach, in the absence of rigorous theoretical conceptualisation this approach contributes little to our understanding of the dynamics of citizens’ political attitudes and behaviour. Moreover, as Leighley and Vedlitz (1999) argue, existing empirical work has been based almost exclusively on the (white) majority population, and it is assumed that SES models operate similarly for minority ethnic groups. The assumption that population parameters are equal across groups is inherently problematic not least because the effects of social background upon levels of civic engagement will reflect respondents’ social and political experiences which are shaped, in part, by ethnic, racial and cultural identities. Psycho-Political Orientations Whilst the SES model has been pre-eminent in the study of citizens’ political participation, other approaches have sought to incorporate attitudinal and affective precursors of political participation (e.g. Aldrich, 1993; Sabucedo & Cramer, 1991; Clarke & Acock, 1989; Jennings & Van Deth, 1989; Abramson, 1983). This approach seeks to understand the ways in which subjective psycho-political factors such as political interest, knowledge, trust and efficacy shape citizens’ participatory decisions. One advantage of this approach is in providing a more secure motivational account of participation since intuitively one might expect that

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respondents who express an interest in politics, or who feel politically efficacious, will be more likely also to participate. In addition to their direct effects, psychological orientations are typically held to have indirect effects upon political engagement by mediating the impact of socio-economic factors. Social Capital Recent years have witnessed an explosion of interest in the UK and internationally in the concept of social capital. As defined by its principal theorists (Coleman, 1988; Putnam, 1993), social capital refers to those features of social organisation - networks of secondary associations, interpersonal trust, norms of reciprocity and mutuality – which act as resources for individuals and facilitate collective action. The general dimensionality of social capital is beyond the scope of this paper (see however Paxton, 2003; Paldam, 2000). However, from the perspective of the study of political behaviour and attitudes, it is evident that civic engagement can be considered both as a product of the accumulation of social capital, and as a constitutive element within the social capital construct. Civic engagement is sometimes considered as a social capital indicator (e.g. Coulthard et al., 2002). At the same time, a wealth of empirical evidence has demonstrated the importance of social capital as an element in the reproduction of democratic political culture both at the individual and aggregate level. In particular, numerous studies have revealed strong associations between political engagement, and measures of neighbourhood trust and associational involvement (e.g. Pattie et al., 2003; Parry et al., 1992; Verba et al., 1995, 1978). In the UK consideration of the relationship between ethnic identity and social capital has received little systematic attention, although to some extent this reflects terminological distinctions. The differential access of minority groups to familial and collective resources, and the extent to which this reflects different ‘value systems’ amongst ethnic minority groups have both received considerable attention (see Solomos & Goulbourne; 2003). However, existing survey analyses certainly do suggest significant ethnic variations in the extent of neighbourhood satisfaction, social trust, informal social contact, and social and community participation (Coulthard et al., 2002). Similarly, based upon a case study approach, recent qualitative research confirms the picture of relatively low levels of grassroots participation in local community networks amongst black Caribbean people – a finding largely attributed to experiences of racism and economic and social marginalisation (Campbell & McLean, 2002). If the impact of variations in social capital is similar across ethnic groups (see above), then we should expect variations in stocks of social capital across ethnic groups to explain a significant proportion of inter-ethnic variance in levels of civic engagement.

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Ethnic Identity One emerging critique of social capital theory within the field of race and ethnic relations has been upon the absence of an historically informed account which gives due weight to experiences of racism, discrimination and group threat in shaping participatory decisions (Solomos & Goulbourne, 2003). However, in the UK context at least, evidence of conflictual inter-ethnic relations is overwhelming (Solomos, 1989; Back & Solomos, 2000), and in various ways draws attention to the potential role of in-group identification, out-group threat and the spatial concentration of ethnic minority communities in shaping patterns of political response. The impact of perceptions of ethnic identity and ‘group threat’ has largely been interpreted in terms of political mobilisation as encouraging collective political action (e.g. Leighley & Velditz, 1999; Giles & Evans, 1985, 1986). However, whilst this is clearly one possibility (as attested by recent anti-racist political mobilisations), at the individual level alienation, and fear of harassment and intimidation, have also been shown to have a negative effect on electoral participation by minority ethnic groups in the UK (e.g. Anwar: 1990, 1994). We therefore expand on this approach to consider whether ethnic identities and perceptions of ‘threat’ are associated with decreased levels of political engagement.

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III: Data, Hypotheses and Operationalisation Dataset The data used to evaluate the models described above are drawn from the 2001 Home Office Citizenship Survey. Overall the sample was designed to be representative of the population of adults aged 16+ living in private households in England and Wales. Based upon the Small Postcode Address File (PAF) two samples were drawn from this population: (a) a nationally representative core sample of 10,015 adults, and; (b) a boost sample of 5,460 minority ethnic adults aged 16 or older. The ethnic minority booster sample was achieved through the use of a focused enumeration sample (derived by screening households proximal to core sample address points), and over-sampling in wards with high ethnic minority population concentration based upon 1991 Census data (18% or more of total resident population). The survey was conducted between 19th March and 6th October 2001 and an effective response rate of 68% was achieved for the core sample (see Smith & Wands, 2003). Dependent Variables In most studies of citizens’ politics, political participation is taken to refer to those actions taken by individuals which seek, more or less directly, to influence public policy (e.g. Verba et al., 1972; Parry et al., 1992). Our primary dependent variable therefore comprises a simple, additive index of seven items designed to tap respondents’ propensity to engage in actions with the goal of influencing policy decisions. Table 1 (below) illustrates some key properties of this eight-point ‘political action’ scale for the combined sample, namely the proportion of all respondents (white and non-white) reporting participation in each of these activities in the last 12 months (Column 1), inter-item correlations (Columns 2-8). Table 1. Key Properties of Political Action Scale

% V1 V2 V3 V4 V5 V6 V7 V1 Contacted a local councillor 9.0 1.00 V2 Contacted an MP 5.2 .296 1.00 V3 Contacted local council official 14.5 .283 .185 1.00 V4 Contacted central government official 2.7 .182 .250 .211 1.00 V5 Attended a public meeting or rally 6.9 .298 .239 .222 .208 1.00 V6 Taken part in a demonstration or protest 1.6 .112 .124 .102 .115 .222 1.00 V7 Taken part in other protest activity 2.3 .180 .182 .114 .114 .244 .159 1.00 Standardised Cronbach’s Alpha= .630 As Table 1 (above) shows, only a small minority of respondents appear to be sustaining the active citizen role. These data have a negative exponential distribution, with a clear majority (61%) of respondents having not undertaken any of these activities within the last 12 months, and a further quarter (25%) having

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undertaken only one of the above activities. However, all measures in the scale are additive (i.e. positively correlated) and the overall reliability of this scale, that is its internal consistency as against all possible indices of a similar size, is reasonably adequate (Alpha=.630) though slightly below the 0.7 threshold often suggested as a useful benchmark for social and psychometric data (e.g. Nunnally, 1978)i However, in addition to examining the overall level of participation, the analyses that follow also investigate the type of participation reported by respondents. Empirical analyses of political participation often distinguish between different forms of participation in order to address the question of whether, and to what extent, individuals specialise in different forms of political action. The conceptual distinction between individualised contacting of public officials and elected representatives (e.g. councillors, MPs, local and central government officials) and protest-type political action (e.g. signing petitions, attending rallies, demonstrations, etc., boycotts, pickets and occupations) is well supported by existing empirical studies (e.g. Verba & Nie, 1972; Verba et al., 1978, 1995; Dalton et al., 1988; Parry et al., 1992; Klingemann & Fuchs, 1995). On the basis of the observed variables described in Table 1 (above) we might therefore hypothesise that these indicators in fact measure two distinct dimensions – individual contacting and political protest – and this is an expectation reinforced by the relatively low Alpha reliability of the simple additive scale. Principal component analysis of tetrachoric correlations between the seven observed variables confirms this expectation. Two factors were extracted with a squared correlation of .653 and an explained variance of 44.7%. The factor loadings suggest that the two factors are readily interpretable in terms of a distinction between individual contacting and protest-type political action, as shown in Table 2 (below). Table 2. Principal Component Analysis of Political Participation Items. Rotated Factor Loadings (Varimax Rotation) Factor 1 – “Contacting” Factor 2 – “Protest” Contacted a local councillor .681 .116 Contacted an MP .635 .127 Contacted local council official .624 .074 Contacted central government official .594 .057 Attended a public meeting or rally .437 .531 Taken part in a demonstration or protest .022 .785 Taken part in other political activity .121 .612 Eigenvalue 2.15 .98 Explained Variance 30.7% 14.0% In the analyses that follow, the unidimensional, additive model of political participation is tested alongside each of these factors using a logit regression approachii. Thus, ‘contact’ describes whether or not respondents reported any political contacting based upon the items described by Table 2 (contacted a local councillor, MP, or local or central government official) – 22.4% of the weighted sample. Similarly, ‘protest’ refers to whether or not respondents had engaged in

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any of the protest-type actions described in Table 2 (public meeting or rally, demonstration, other political action) – 26.3% of the weighted sample. Independent Variables A wide range of indicators of socio-economic status and social position are available. However, studies of political participation invariably identify both social class and educational achievement as key determinants of individual’s propensity to engage in political action (e.g. Parry et al., 1992; Dalton, 1988; Barnes & Kaase, 1979; Verba et al., 1995). Measurement of social class is based upon National Socio-Economic Classification (ONS, 2004). This approach is a modified version of the ‘Goldthorpe Schema’ (1980/87), a widely accepted occupationally based approach to the measurement of social class. In particular, the analyses that follow distinguish between respondents in manual (26% of the sample) and non-manual occupational groups (MANUAL). Educational achievement is here measured by respondent’s highest educational qualification to date, distinguishing between respondents educated to degree HE diploma level or higher (27% of the sample), and all other respondents (DEGREE). With regard to the social capital model, both behavioural and attitudinal measures are used here in order to uncover the extent of both positive affective ties to neighbourhood and community, and actual face-to-face social interaction within communities. The social capital approach is conceptualised here in relation to four inter-related dimensions: social participation; neighbourhood satisfaction; associational involvement, and; social networks. Social participation is operationalised by three variables which measure the frequency of respondents socialising with friends or neighbours: (a) at the respondent’s home; (b) at a friend’s home, and; (c) elsewhere (e.g. pub, restaurant, etc.)iii. These indicators were then combined in a simple additive scale with values ranging from 3 to 21 (PARTICIP). The reliability of the resultant scale is high (Alpha=.73), suggesting that a single common factor explains most of the variance across these indicators. A variety of indicators of neighbourhood satisfaction are available for analysis based upon the 2001 HOCS, and responses have been combined to form a weighted aggregate scale, with values in the range 0-17 (NEISCAL). The individual components are Likert-type scales, measuring respondent’s perceptions of (a) whether people in the local neighbourhood can be trusted; (b) whether people look out for each other; (c) whether they would return a lost wallet, and; (d) the number of people known to respondent in the neighbourhood. As with social participation, the scale reliability is also high (Alpha=.71). In addition, and in line with existing findings, length of residence in the area in years is also hypothesised to be positively correlated with political action (RESLEN).

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The third component of the social capital model, associational involvement, is measured by whether respondent’s had participated in a wide variety of community, social, civic, creative, sporting, faith-based or other organisation in the last 12 monthsiv. Responses to these items were again summed to produce a 14-point index of associational involvement (ASSOC). In the regression models that follow a natural log transformation has been applied so that these data approximate more closely to the underlying assumption of normality. As with the other social capital scales, the reliability of this scale is also reasonably good (Alpha=.66). Finally, social networks are operationalised by two variables measuring the number of relatives with whom the respondent has contact on at least a monthly basis, and the number of relatives who have given the respondent practical help or support within the last twelve months. Responses have been summed to produce a 30-point aggregate scale with a high degree of item reliability (Alpha=.71) (NETWORKS). Indicators of psycho-political orientations measure respondent’s trust in public institutions, namely, police, courts, parliament, politicians and local government (POLTRUST), and perceptions of personal political efficacy (EFFICACY). Trust in public institutions is measured by five, 4-point Likert-type items, and responses have been aggregated to comprise a 20-point scale with a high degree of internal reliability (Alpha=.77). As Campbell et al. (1954: 187) argue, political efficacy refers to

The feeling that individual political action does have, or can have, an impact upon the political process…It is the feeling that political and social change is possible and that the individual citizen can play a part in bringing about this change

Items measure respondents perceptions of their capacity to influence local and national political events have been combined to produce a 6-point scale with a reasonably high degree of internal reliability (Alpha=.70). Table 3 (below) shows individual scale items for political trust and efficacy and the proportion of respondents agreeing or agreeing strongly with propositions relating to political trust and efficacy by ethnic group. These results show that with the exception of trust in the police (and, for black respondents, the courts) minority ethnic groups are more likely to trust public institutions, and to feel politically efficacious, than white respondents. Table 3. Political Trust and Efficacy by Ethnic Group (% agree/agree strongly)

White Asian Black Other Trust in police 81 78 60 74 Trust in courts 72 79 62 76 Trust in politicians 22 33 29 30 Trust in parliament 35 55 44 51

TRUST

Trust in local council 51 64 63 60 Able to influence local decisions 43 46 52 49 EFFICACY Able to influence national decisions 24 32 35 33

All associations significant at .001 level (Pearson Chi Square)

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Lastly, the ethnic identity and group cohesion model is operationalised by three variables measuring: (a) the concentration of ethnic minority households within respondent’s local area (ETH_AREA); (b) respondents’ perceptions of racial discrimination in the delivery of local services (SERVICES), and; (c) respondent’s perceptions of the salience of ethnic group, country of origin, nationality, religion and colour in shaping personal identity (ETH_ID). In the absence of linking data from the 2001 Census, ethnic minority population concentration is here based upon the ACORN classification of area types. The classification of respondents is based upon areas identified as ‘ethnic minority’ areas within the ACORN classification (Clusters 20, 24, 36, 38, 44, 52, 53, 54), resulting in a binary (yes/no) indicator where 7% of the combined sample live in areas with high ethnic minority concentrations. By ethnic group, the proportion of respondents living in neighbourhoods classified as ‘ethnic minority’ areas are respectively 4% (white), 56% (Asian), 49% (black), and 30% (other non-white). Perceptions of racial discrimination are measured by asking respondents whether, in their experience, someone like themselves would be treated better, worse or the same as other racial groups in relation to a range of 19 essential local servicesv. Responses to these items have been aggregated to produce an highly reliable (Alpha=.91) index of perceived institutionalised discrimination at a local level with values in the range 0 to 38. One-way analysis of variance reveals significant and substantial variation in perceptions of discrimination across ethnic groups, with ethnic minority respondents reporting significantly higher levels of discrimination than whites (F=181.8, p<.001). By ethnic group, the proportion of respondents reporting levels of discrimination in service delivery greater than the sample mean was respectively 36% (white), 67% (Asian), 79% (black), and 71% (other non-white). With respect to the salience of ethnic identity, survey respondents were also asked what they considered to be the most important aspects when describing themselves. Responses were not mutually exclusive thus resulting in a series of binary variables amenable to exploratory factor analysis. Principal component analysis of tetrachoric correlations extracted two significant latent variables with a squared correlation of .648, accounting for 33.1% of total variance (see Table A1, Appendix). The first factor (accounting for 18.0% of total variance) relates primarily to age, employment, education, income, gender, and personal interests as significant dimensions of personal identity. The second factor (accounting for 15.1% of total variance) refers to ethnic/cultural identity, familial country of origin, nationality, religion and colour as significant dimensions of personal identity. Standardised factor scores for this latter ‘ethnic identity’ latent variable have employed in the regression analyses that follow. (Table A2 presents summary characteristics for all variables used in the analyses below).

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Explanatory Models and Hypotheses Table 4 (below) summarises the key features of these competing models, their formal specification, and the key hypotheses associated with each of these approaches. Positive relationships are hypothesised between political action and each of the individual components of the SES and social capital models. In contrast, the impact of political trust upon levels of political action is more difficult to evaluate. Intuitively, as a measure of political affect, trust in public institutions might be assumed to be positively correlated with political action, and this is the assumption made below. However, political cynicism is sometimes viewed as evidence of citizens’ political sophistication, and one implication of policy dissatisfaction models (e.g. refs) may thus be that politically trusting citizens are more content to leave politics to their elected representatives. Similarly, the effects of discrimination in the delivery of local services are hypothesised to exert a negative effect on levels of political engagement. Again, it is possible to view such experiences as constituting a powerful motive for political action, and at the collective level this has certainly been a key impetus behind minority ethnic political mobilisations (e.g. Solomos, 1988). However, at the individual level the impact of exclusionary practices is by definition to diminish individual’s propensity to participate in wider society, including political participation. Table 4. Summary of Models. MODEL COMPONENTS HYPOTHESISED EFFECT

Social class + Educational achievement + SOCIO-ECONOMIC

STATUS Length of residence + Neighbourhood satisfaction + Associational Involvement + SOCIAL CAPITAL Social Participation + Trust in political institutions + PSYCHO-POLITICAL

ORIENTATIONS Political efficacy + Minority ethnic concentration + Discrimination in local services

- GROUP IDENTITY AND COHESION

Ethnic/religious identity +

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IV: Testing the Alternative Models Typically, multivariate approaches to the study of ethnic minority political engagement include additional dummy variables for ethnic group alongside other theoretically significant predictors of participation. Amongst other things, this approach assumes the population parameters for the other theoretically significant predictors are equal across groups. However, as Leighley and Velidtz (1999) argue, if individuals’ social and political experiences are shaped partly by their ethnic identities, then this assumption is clearly questionable. In order to address this issue, the above models are assessed separately for each ethnic grouping. In doing so, this approach seeks to validate existing theories by determining their generalisability across different ethnic groups. This approach is especially important since ‘general’ theories are often based upon essentially homogenous populations, either being based upon a representative sample (i.e. effectively the white population), or upon specific ethnic sub-groups in which it is almost impossible to systematically address inter-ethnic variance in participation due to variations in timing, sampling methodologies and contextual factors across surveys. Modelling of ‘overall’ political participation using the additive index is based upon ordinary least squares (OLS) linear regression. Thereafter, since the focus here is upon types of participation rather than their level, binary logistic regression is used to estimate whether or not participants had engaged in political contacting or political protest. In total, nearly one quarter (23%) of respondents had engaged in political contacting by getting in touch with a local councillor, MP, or local or central government official about a matter of concern to them. A similar proportion (26%) had attended a protest meeting, rally, demonstration or similar protest activity within the last twelve months. For all three variables - overall participation, political contacting and political protest – statistically significant ethnic differences in the extent of participation were evident, as detailed in Table 5 (below). Table 5. Overall Participation, Contacting and Political Protest by Ethnic Group Overall Participation Contact Protest (Mean) (%) (%) White .64 22.9 26.7 Asian .41 17.1 15.6 Black .43 19.0 17.0 Other non-white .42 17.7 16.3 Test Statistic F=12.3 χ²=12.47 χ²=45.46 Sig. <.001 <.01 <.001

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V: Presentation of Findings Participation Examined with Separate Ethnic Samples We first estimate an OLS regression model that tests each of the above models for each ethnic group separately, and for the sample as a whole, for the participation variable. Overall, the SES, social capital, and political attitudes models are strongly supported, with strong positive relationships evident in relation to education (DEGREE), associational involvement (ASSOC), political efficacy (EFFICACY), and political trust (POLTRUST) (Table 6, below)vi. Respondents with higher levels of human, social, and psycho-political resources participate more, and these relationships hold across ethnic groups. The social capital model, which has been extensively tested in other sample studies of the UK’s predominantly white population, is partially confirmed by these analyses. Associational involvement (ASSOC) is the single most powerful predictor of political participation across all ethnic groups. Similarly, extensive familial networks of social support (NETWORK) are also a significant predictor of political participation for all ethnic groups. In contrast, however, neither neighbourhood satisfaction (NEISCAL), nor social participation (PARTICIP), show a consistent and significant pattern of influence across ethnic groups. Although, as expected, length of residence is positively associated with political participation both for the sample as a whole and for white respondents, results are not significant for other ethnic groups. Table 4: Main Effects Model Estimated Separately by Ethnic Group- OLS Regression.

White Asian Black Other ALL Beta Beta Beta Beta Beta

Main Effects: DEGREE .108 .063 .089 .066 .107 MANUAL -.022 -.047 [.041] [-.030] -.023 RESLEN .034 [.032] [.018] [.026] .033 NEISCAL [-.017] [.030] [.022] [-.053] -.016 PARTICIP [.015] [-.011] [-.002] [.003] [.014] ASSOC .239 .189 .175 .196 .236 NETWORK .066 .074 .130 .148 .067 POLTRUST .108 .097 [.037] .107 .106 EFFICACY .120 .090 .073 [.047] .117 SERVICES [.009] [-.029] [.020] [-.011] [.009] ETH_AREA .046 [-.007] [.026] [.054] .046 ETH_ID .023 .046 [.015] .096 .026 ASIAN - - - - -.042 BLACK - - - - -.030 OTHER NON-WHITE - - - - -.017 F Change 116.7 30.6 13.9 13.2 154.3 R² .131 .103 .084 .140 .131 N 8,879 3,211 1,830 990 15,475 [ ] Not significant at .05 level

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The above hypotheses concerning the effects of psycho-political orientations upon levels of overall participation in politics are generally supported, both in relation to political efficacy (EFFICACY) and political trust (POLTRUST) across all ethnic groups. Estimates are non-significant at the .05 level for black respondents (POLTRUST) and other non-white respondents (EFFICACY). This suggests that whilst levels of political trust and efficacy are generally high amongst black and other non-white respondents, this has only a negligible impact upon their levels of political action. However, in all cases, respondents who are sanguine about their capacity to influence national and/or local decisions participate more, as do respondents with relatively high levels of trust in public institutions such as the police, courts, parliament, politicians and their local council. In contrast, the results are much more mixed in relation to the ethnic identity hypotheses outlined above. Here we find no consistent, significant pattern across ethnic groups. Perceptions of discrimination in public service delivery (SERVICES) are mixed in their effects upon the level of respondents’ political participation, and results are not significant either for the sample as a whole or for ethnic sub-groups. Living in an area of high ethnic minority concentration appears to exert a moderate positive effect upon levels of political participation for white respondents but no significant relationship is evident for minority ethnic respondents themselves. Finally, a strong sense of ethnic and cultural identification (ETH_ID) is positively associated with higher levels of participation for all ethnic groups, though the relationship is not significant for black respondents and, with the exception of ‘other’ ethnic minority respondents, parameter estimates are not substantial. Overall, the results presented in Table 6 (above) strongly support the socio-economic status, psycho-political and social capital models of citizens political behaviour across ethnic groups, with much less support for the ethnic identity approach. However, in terms of model fit it is clear that these approaches are not equally appropriate across ethnic groups. The overall fit of the models is relatively weak for the sample as a whole (R sq.=.131). However, for Asian and black respondents conventional explanations of political participation are less appropriate, accounting for only 10% and 8% respectively of the variance in levels of participation (R sq.=.103 and .084). In particular, conventional accounts appear to be least successful in accounting for the political participation of black respondents for whom neither political trust or ethnic identity appear to exert a significant influence. A failure to take account of the distinctive motivational bases of participation across minority ethnic groups can therefore result from over-generalised accounts of participation. Participation Examined with Pooled Sample and Use of Interaction Terms However, the parameter estimates outlined in Table 4 (above) should be treated with caution since they are based upon different regression equations. As Leighley

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and Velditz (1999) suggest, a more rigorous strategy involves pooling ethnic groups then estimating a combined model with interaction terms fitted for each ethnic group and variable. In principle, this would therefore involve fitting interaction terms for each minority ethnic group plus the original variable - in this case resulting in 48 independent variables (12 original variables +(12*3) interaction terms). However, such an approach is likely to produce some biased estimates by chance at the 95% confidence level, given the large number of predictors. Moreover, estimates are also biased as a result of the confounding effects of including multiple highly correlated independent variables (multicollinearity) – as confirmed by analysis of tolerance values and condition indices. Following Velditz and Leighley (1999), an alternative solution is adopted here based upon comparison of sets of coefficients. In Table 5 (below) ethnic samples are pooled and results compared for the basic model (as outlined in Table 2) plus dummy variables for Asian, black and ‘other’ minority ethnic groups, plus interaction terms for each ethnic group separately – resulting in three models with 27 predictor variables in each model (12 original variables + 3 dummy variables + 12 interaction terms). As a first step, the basic models for the level of overall participation (Model A), and the likelihood of political contacting (Model B) and protest (Model C), are estimated for the pooled sample with dummy variables for each minority ethnic group. The effects of including the 12 interaction terms for each minority ethnic group are evaluated via examination of model statistics. In this case of overall participation this is based upon comparison of the difference in residual sum of squares between the basic and interactive models and the associated F-statistic. For political contacting and protest, based upon logit regression, equivalent model statistics are examined (-2LL and model Chi square respectively). The F-statistic/Chi square describe whether the model better predicts the level and type of participation of minority ethnic groups compared with the main-effects only model. In effect, a significant test statistic indicates that the factors facilitating political participation differ significantly for the ethnic group under consideration in comparison with white respondents. In general, and with respect to the main effects only models, results are generally consistent with earlier findings. In terms of overall participation (Model A), socio-economic status, psycho-political and social capital models are all supported by these analyses with significant parameter estimates for all variables except social participation (PARTICIP) and neighbourhood satisfaction (NEISCAL). In contrast, ethnic identity variables have a lesser influence upon levels of participation, although with the exception of perceptions of discrimination in service use (SERVICES) all estimates are significant. Secondly, Asian, black and ‘other’ minority ethnic respondents participate at lower levels than white respondents even when controlling for variations in social status and human, social and psycho-political resources. Again, this finding confirms earlier results (see however Leighley & Velidtz (1999)).

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The impact of ethnic status upon the odds of political contacting (Model B) and political protest (Model C) appear to be broadly similar, with Asian, black and other non-white respondents being considerably less likely to report participation than whites. However, with regard to the general hypotheses summarised in Table 4 (above) some significant variations are evident between the two forms of participation. Firstly, the socio-economic status model (measured by DEGREE & MANUAL) appears to be a more powerful predictor of political contacting than political protest. Secondly, with respect to the social capital model, associational activity (ASSOC), collective political efficacy (EFFICACY) and political trust (TRUST) are all more powerful predictors of protest activity than they are of political contacting. In contrast, and contrary to expectations, the influence of social participation is negative with respect to the likelihood of political protest suggesting that rising levels of social participation ‘crowd out’ protest action. However, the direction of effect is reversed with respect to political contacting. Finally, in relation to the group identity model, living in an area of ethnic minority concentration has a positive impact upon the likelihood of political contacting, but results are non-significant at the .05 level for political protest. Table 5: Main Effects and Saturated Models of Participation. A) ALL B) Contact C) Protest B B (logit) B (logit) Main Effects: DEGREE .107 .226 .122 MANUAL -.023 -.050 -.073 RESLEN .033 .110 [.022] NEISCAL [-.016] [.018] [-.041] PARTICIP [.014] .086 -.074 ASSOC .236 .362 .562 NETWORK .067 .109 .191 POLTRUST .106 .145 .266 EFFICACY .117 .175 .245 SERVICES [.009] [-.024] [.037] ETH_AREA .046 .062 [.017] ETH_ID .026 .070 .040 ASIAN -.042 -.071 -.092 BLACK -.030 -.049 -.060 OTHER NON-WHITE -.017 -.032 -.044 CONSTANT [<.001] -1.315 -1.196 F statistic/Chi Sq. 154.3 875 1,799 R sq./Nagelkerke R Sq. .131 .086 .168 Residual Mean Square/-2LL 13,427 14,916 14,668 Interactions – Other non-white F statistic/Chi Sq. 82.9 [13.4] [13.6] Residual Mean Square/-2LL 12,530 14,903 14,653 Interactions – Asian F statistic/Chi Sq. 83.7 21.7 65.9 Residual Mean Square/-2LL 12,515 14,895 14,602 Interactions – Black F statistic/Chi Sq. 84.0 57.7 [15.7] Residual Mean Square/-2LL 12,510 14,858 14,652 [ ] Not significant at .05 level (one tail)

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However, we are primarily concerned here with the extent to which the subset of ethnic group interactions better predict the type and extent of ethnic minority participation in comparison with the main effects only models. With regard to the overall level of respondents’ participation (Model A), Table 5 (above) shows that all three sets of ethnic group interactions are significant at the 0.1% level of significance, indicating that we can better understand the process of ethnic minority political mobilisation by examining these interactions. However, results are more mixed with respect to understanding the type of participation using logistic regression with Maximum Likelihood estimation (Models B and C). Thus, the effects of ethnic interactions upon the odds of political contacting (Model B) differ substantially across ethnic groups. Interactions for Asian and black respondents both have a significant impact upon the odds of political contacting, and effects (based upon Model Chi square statistics) are especially large for black respondents. This suggests that the factors facilitating political contacting differ significantly in their effects for black and Asian respondents compared with other ethnic groups. In contrast, including interaction terms for other non-white respondents within the model of political contacting has no significant impact upon overall model fit. As with political contacting, the effects of ethnic interactions upon the odds of political protest (Model C) differ substantially across ethnic groups. In fact, for neither black nor other non-white respondents does inclusion of interaction terms produce a significant improvement in model fit. In contrast, interactions for Asian have a significant impact upon the odds of political protest. We may conclude therefore that ethnicity has a significant impact upon the process of political mobilisation for black and Asian respondents with respect to political contacting, and for Asian respondents with respect to political protest. However, not all of the twelve ethnic group interaction terms are significantly associated with the level and type of respondents’ political participation. In Table 6 (below) these analyses are repeated by comparing the main effects only models with models of overall participation, political contacting and political protesting including both main effects and those interaction terms significant at the .01 level. These data suggest that ethnic group interactions vary both within groups in relation to the nature and level of participation, as well as across groups. For Asian respondents, several significant interactions condition the relationship between human, social, and psycho-political resources and the level of respondents’ political participation (Model A). Interactions between ethnic status and educational level (DEGREE), neighbourhood satisfaction (NEISCAL), associational involvement (ASSOC), perceptions of discrimination in service delivery (SERVICES), and living in an area of high ethnic concentration (ETH_AREA) are all important in predicting the level of overall participation. In contrast, and with the exception of perceptions of service discrimination

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(SERVICES), no group interaction effects have a significant impact upon the likelihood of political contact for Asian respondents (Model B). However, being Asian appears to have a substantial impact upon the many of the key social predictors of the likelihood of political protest (Model C). As with overall participation, interactions between ethnic status and perceptions of discrimination in service delivery (SERVICES), and (especially) living in an area of high ethnic concentration (ETH_AREA), are both predictors of the odds of political protest for Asian respondents. However, living in an area of high ethnic concentration has a substantial negative effect on the likelihood of political protest for Asian respondents, counter to the group identity/cohesion hypothesis outlined above. Data limitations mean that this variable measures the general concentration of minority groups rather than the concentration of the respondent’s ethnic reference group in the respondent’s neighbourhood. Moreover, this negative effect may reflect also the confounding effect of high levels of area deprivation in areas of high minority ethnic concentration (though no similar effect is evident for black and other non-white respondents). Finally, and in line with expectations, whilst ethnic identity (ETH_ID) has a negligible impact on the odds of political protest for the sample as a whole, the effect is both substantial and positive for Asian respondents.

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Table 6: Fitted Models of Political Participation, Contacting and Protest. A) ALL B) Contact C) Protest B B (logit) B (logit) Main Effects: DEGREE .105 .229 .114 MANUAL -.031 -.088 -.071 RESLEN .030 .112 [.021] NEISCAL [-.013] [.018] -.043 PARTICIP [.007] .087 -.048 ASSOC .242 .364 .561 NETWORK .069 .111 .174 EFFICACY .105 .178 .257 POLTRUST -.106 -.201 -.243 SERVICES [.012] -.048 .075 ETH_AREA .054 .063 [.063] ETH_ID .035 .061 .002 ASIAN -.064 -.071 -.111 BLACK -.086 -.048 -.053 OTHER NON-WHITE -.027 -.044 -.044 Constant [.003] -1.324 -1.192 Interactions Other non-white*Eth_id - .144 - Other non-white*Network .021 - - Other*Efficacy .020 - - Asian*Degree -.026 - - Asian*Neiscal .017 - - Asian*Assoc -.030 - - Asian*Particip - - -.032 Asian*Services -.020 .026 -.039 Asian*Eth_area -.044 - -.484 Asian*Eth_id - - .147 Black*Manual .030 .661 - Black*Network .021 - .049 Black*Poltrust -.026 -.056 - Black*Efficacy - -.112 - F statistic/Model Chi Sq. 88.8 925 1,847 R square/ Nagelkerke R Sq. .131 .091 .172 Residual Mean Square/-2LL 23,937 14,866 14,618 [ ] Not significant at .05 level (one tail)

For black respondents, manual occupational status (MANUAL) has a significant positive impact both upon the overall level of respondents’ participation (Model A) and (especially) in relation to the likelihood of political contacting (Model B). Similarly, and contrary to expectations, both political trust (POLTRUST) and political efficacy (EFFICACY) appear to have a negative impact upon the odds of political contacting for black respondents in strong contrast with the sample as a whole (Model B). This may reflect satisfaction with the performance of political office holders, or the persistence of deferential attitudes, though in both cases further research is clearly necessary in order to explain why this varies across ethnic groups. It is worth noting that, with the exception of the effects of strong social networks (NETWORK), no group interactions have a significant impact upon the odds of political protest for black respondents (Model C). With regard to

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other non-white respondents, only political efficacy (EFFICACY) and social networks (NETWORK) have a significant impact upon the overall level of respondents’ participation (Model A). In addition, living in an area of high ethnic concentration (ETH_AREA) has a positive impact upon the odds of political contacting (Model B).

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VI: Interpretation of Findings The findings described here show that minority ethnic British citizens participate less in political life than the majority white population. Overall, minority ethnic groups are both less likely to contact their political representatives and public officials, and to engage in protest-type political action such as attending public meetings, demonstrations and other forms of protest activity. Overall levels of political participation are also lower amongst ethnic minority groups in Britain. To this extent, these findings largely confirm the results of earlier studies – both quantitative and qualitative - of ethnic minority political participation and political mobilisation, both in Britain and elsewhere (e.g. Saggar, 1991, 1992, 1998; Anwar, 1990, 1994, 2001; Solomos et al., 2002; Bousetta, 2002; Electoral Commission, 2002; Leighley & Velditz, 1999; Barkan, 1998; Le Lohe, 1998; Zig, 1990). Existing research into political engagement amongst Western publics typically refer to the importance of socio-economic status (e.g. social class, educational achievement), social capital (e.g. associational involvement, social networks and participation, neighbourliness) and psycho-political attitudes (e.g. political trust, political efficacy) in determining the nature and extent of citizens’ political participation. In contrast, rather less attention has focused upon how and to what extent the above factors shape the political participation of ethnic minority citizens in Britain, partly as a result of limited sample sizes and inappropriate sampling methods. The main focus of this paper has been to examine the robustness of four competing models of political participation across ethnic groups in Britain. The socio-economic status, social capital, and psycho-political attitudes models all receive relatively strong support across ethnic groups from the analyses presented here. The group identity model is in general not well supported. With the exception of ethnic/religious identity (which has a moderate positive effect on the political participation of Asian, white and ‘other’ non-white respondents), results are not significant save for white respondents living in areas of high minority ethnic concentration. This is important because it suggests that whilst a strong sense of ethnic identity is an important driver of political participation both for ethnic minority groups and for the white population, living in ethnically diverse communities does not affect the extent of minority ethnic citizens’ political participation to a significant extent. However, the substantial interaction effect for Asians with respect to political protest suggests that it may it may partly determine the form this takes for Asian citizens. However, and whilst these factors are important in shaping ethnic minority political participation, the results reviewed above suggest both that their explanatory power is somewhat limited in comparison with white British citizens, and that their effects vary in across minority ethnic groups. As a result, in order to more fully understand the process of ethnic minority political mobilisation, further

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disaggregated analyses of specific ethnic minority populations are needed, specifically with a view to exploring the ways in which ethnicity interacts with individuals’ human, social, and psycho-political resources in shaping patterns of political engagement and participation. The analyses presented here show that ethnic status interacts in significant ways with individuals’ socio-economic status, access to social capital, political attitudes, and ethnic identity and group cohesion in determining both the level and type of ethnic minorities’ political participation. This is true for all non-white ethnic groups in relation to the extent of their participation, and also helps determine the type of participation in relation to political contacting for black and Asian respondents, and political protest for Asian respondents. Further Research Clearly, the way ethnic status is operationalised is crucial. Ideally, and with still larger sample sizes, a more sophisticated approach to the measurement of ethnic groups which disaggregates Asian, black and ‘other non-white’ respondents is necessary to fully explore the relationship between ethnicity and political participation. Similarly, it should be acknowledged that these findings relate only to a fairly restricted range of indicators of political contacting and political protest, and that a broader range of indicators would be preferable both from a technical viewpoint - in terms scale reliability, and from a theoretical perspective – for example, in order to explore the relationship between ethnicity and electoral participation, party political involvement, etc. Furthermore, investigation of the interactions between ethnicity and human, social, psycho-political and collective resources in shaping patterns of political participation by definition raises the possibility of multicollinearity in the context of regression analysis. Whilst inspection of collinearity diagnostics did not identify substantial multicollinearity in these data, the possibility of higher-order collinear effects cannot be ruled out altogether. Potentially, this approach could be usefully extended through the use of partial least squares methods and ridge regression although, as variants of the general linear model, neither of these approaches represents an ideal solution.

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Appendix Table A1: Principal Component Analysis of Self-Identity Items. Rotated Factor Loadings (Varimax Rotation) Factor 1 –

“Ethnic/Religious” Factor 2 –

“Socio-Economic” Age or life-style .123 .541 Type of work -.006 .650 Level of education .210 .613 Level of income .241 .519 Interests .033 .563 Gender .328 .507 Ethnic group or cultural background .674 .147 Country of family origin .664 -.012 Nationality .587 .114 Religion .564 -.024 Colour of skin .667 .126 Family .139 .139 Social class .423 .296 Disability status .388 .085 Sexuality .464 .276 Eigenvalue 3.57 1.41 Explained Variance 22.3% 13.7% Table A2: Variables Used in Regression Analyses: Summary Statistics.

Range Min. Max. Mean Std. Dev.

Scale Alpha

Action 7.00 0.00 7.00 0.62 1.03 .630 Contact 1.00 0.00 1.00 0.22 0.42 - Protest 1.00 0.00 1.00 0.26 0.44 - Degree 1.00 0.00 1.00 0.27 0.44 - Manual 1.00 0.00 1.00 0.26 0.44 - Reslen 94.00 0.00 94.00 17.48 16.35 - Neiscal 17.00 1.00 18.00 9.52 2.76 .712 Particip 18.00 3.00 21.00 12.57 4.35 .734 Assoc 14.00 0.00 14.00 1.67 1.88 .663 Network 30.00 0.00 30.00 5.31 3.75 .714 Efficacy 5.00 1.00 6.00 3.85 1.55 .701 Poltrust 19.00 1.00 20.00 11.97 3.19 .771 Services 38.00 0.00 38.00 18.74 5.49 .910 Eth_area 1.00 0.00 1.00 0.07 0.26 - Eth_ID 5.95 -1.26 4.69 0.03 1.02 -

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i In the OLS regression analyses that follow, a natural log transformation has been applied to these data in order to approximate more closely to underlying assumptions of bivariate normality. ii Values for political efficacy have been imputed in approximately 5% of cases based on regression imputation, since one-way ANOVA revealed that missing values were not randomly distributed. Evaluation of regression assumptions resulted in a natural log transformation of the dependent variable, and of associational involvement, in order to reduce skewness, and improve the normality, linearity and homoscedasticity of residuals. Analysis of multi-collinearity was also undertaken based upon inspection of simple Pearson correlations, tolerance statistics, and collinearity diagnostics. iii The social participation items were coded as follows: every day; several times a week; once a week; once a fortnight; once a month; less than once a month; never. iv Associational involvement is measured by participation in the following organisations: (1) children’s education/schools; (2) children’s and young people’s activities (outside school); (3) education for adults; (4) sports/exercise; (5) religion; (6) health, disability and social welfare; (7) the elderly; (8) safety and first aid; (9) the environment and animals; (10) justice and human rights; (11) local community groups; (12) citizen’s groups; (13) hobbies, recreation, arts and social; (14) trade union activity. v These local services are: GP practice; hospital; school; council/HA housing services; local council; private landlord/letting agent; Armed Forces; bank/building society; supermarket chain; insurance company; petrol station; Courts (Magistrate/Crown Court); Crown Prosecution Service; Home Office; Police; Fire Service; Immigration authorities; Prison Service; Probation Service. vi It is well known that the social antecedents of political participation explain only a relatively small proportion of the total variance in overall levels of political activity in Britain (eg. Pattie et al., 2003). In this context, beta weights of greater than .1 are thus described a relatively strong relationships.

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References Abramson, P. (1983). Political Attitudes in America, San Francisco: Freeman. Aldrich, J. (1993). Rational Choice and Turnout. American Journal of Political Science 37(1): 246-278. Ali, R. & O'Cinneide, C. (2002). Our House? Race and Representation in British Politics. London: Institute of Public Policy Research. Anwar, M. (1986). Race and Politics: Ethnic Minorities and the British Political System. London: Tavistock. Anwar, M. (1990). 'Ethnic Minorities and the Electoral Process: Some Recent Developments'. In H. Goulbourne (Ed.) Black Politics in Britain, London: Gower. Anwar, M. (1994). Race and Elections: The Participation of Ethnic Minorities in Politics. Coventry, University of Warwick. Anwar, M. (2001). The participation of Ethnic Minorities in British Politics. Journal of Ethnic and Migration Studies 27(3): 533-549. Back, L. & Solomos, J. (2000). Theories of Race and Racism: A Reader. London: Routledge. Barkan, S. (1998). Race, Issue Engagement and Political Participation: Evidence form the 1987 General Survey. Race & Society 1(1): 63-76. Barnes, S. & Kaase, M. (1979). Political Activity: Mass Participation in Five Western Democracies. London: Sage. Bousetta, H. (2002). Extending Democracy: Participation, Consultation and Representation of Ethnic Minority People in Public Life. Bristol: University of Bristol. Brady, H., Verba, S. & Schlozman, K. (1995). Beyond SES: A Resource Model of Political Participation. American Political Science Review 89: 271-94. Campbell, C. & McLean, C. (2002) Ethnic Identities, Social Capital and Health Inequalities: Factors Shaping African-Caribbean Participation in Local Community Networks in the UK. Social Science and Medicine 55(4): 643-657. Catt, H. (1996). Voting Behaviour: A Radical Critique. London: Leicester University Press.

25

Clarke, H. & Acock, A. (1989). National Elections and Political Attitudes. British Journal of Political Science 19: 551-562. Coulthard, M., Cooper, A. & Morgan, A. (2002). People's Perceptions of their Neighbourhood and Community Involvement: Results from the Social Capital Module of the General Household Survey 2000, London: The Stationary Office. Dalton, R. (1988). Citizen Politics in Western Democracies. New Jersey: Chatham House. Electoral Commission (2002). Voter Engagement Amongst Black and Minority Ethnic Communities. London, Electoral Commission. Goldthorpe, J. (1997) “The ‘Goldthorpe’ Class Schema: Some Observations on Conceptual and Operational Issues”. In D. Rose & K. O’Reilly (Eds). Constructing Classes: Towards a New Social Classification for the UK. Swindon: ESRC/ONS. Goldthorpe, J. (1980/1987). Social Mobility and Class Structure in Modern Britain. Oxford: Clarendon. Smith, P. & Wands, S. (2003). Home Office Citizenship Survey, 2001 – Technical Report. London: Home Office/BMRB International. Jennings, M. & Van Deth, W. (Eds.) (1989). Continuities In Political Action. Berlin: De Gruyter. Kotler-Berkowitz, L. (2001). Religion and Voting Behaviour in Great Britain: A Reassessment. British Journal of Political Science 31: 523-554. Leighley, J. & Vedlitz, A. (1999). Race, Ethnicity and Political Participation: Competing Models and Contrasting Explanations. The Journal of Politics 61(4): 1092-1114. Le Lohe, M. (1998). Ethnic Minority Participation and Representation in the British Electoral System. In S. Saggar (Ed.) Race and British Electoral Politics. London: University College London Press. Lochner, K., Kawachi, I. & Kennedy, B. (1999). Social Capital: A Guide to its Measurement. Health and Place 5: 259-270. McMiller, D. (2000). Race, Associational Involvement and Political Participation. Race & Society 2(1): 83-95. Marsh, A. (1990) Political Action in Europe and the USA. Basingstoke: Macmillan.

26

Nunnally, J. (1978). Psychometric Theory. New Delhi: Tate McGraw-Hill. ONS (Office for National Statistics) (2004). The National Statistics Socio-Economic Classification User Manual. London: ONS. Paxton, P. (1999) Is Social Capital Declining in the United States? American Journal of Sociology 105: 88-127. Paldam, M. (2000) Social Capital: One or Many? Definition and Measurement. Journal of Economic Surveys 14(5): 629-653. Parry, G., Moyser, M., et al. (1992). Political Participation and Democracy in Britain. Cambridge, Cambridge University Press. Pattie, C., Seyd, B. & Whiteley, P. (2003). Citizenship and Civic Engagement: Attitudes and Behaviour. Political Studies, 51: 443-468. Sabucedo, J. & Cramer, D. (1991). Sociological and Psychological Predictors of Voting in Great Britain. Journal of Social Psychology 131: 647-654. Saggar, S. (1991). Race and Public Policy. Aldershot, Avebury. Saggar, S. (1992). Race and Politics in Britain. London: Harvester Wheatsheaf. Saggar, S. (1998a). The General Election 1997: Ethnic Minorities and Electoral Politics. London: Commission for Racial Equality. Saggar, S., Ed. (1998b). Race and British Electoral Politics. London: University College London Press. Saggar, S. (2000). Race and Representation: Electoral Politics and Ethnic Pluralism in Britain. Manchester: Manchester University Press. Solomos, J. (1988). Black Youth, Racism and the State: The Politics of Ideology and Policy. Cambridge: Cambridge University Press. Solomos, J. & Goulbourne, H. (2003). Families, Ethnicity and Social Capital. Social Policy and Society 2(4): 329-338. Verba, S. & Nie, N. (1972). Participation in America: Political Democracy and Social Equality. Chicago: University of Chicago. Verba, S., Nie, N. & Kim, J.-O. (1978). Participation and Political Equality: A Seven-Nation Comparison. Cambridge: Cambridge University Press.

27

Verba, S., Schlozman, K. & Brady, H. (1995). Voice and Equality: Civic Voluntarism in American Politics. Cambridge, Mass.: Harvard University Press. Zig, L. (1990). “Black Electoral Participation: An Analysis of Recent Trends”. In H. Goulbourne (Ed.) Black Politics in Britain. Aldershot: Avebury.

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