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Inclusiveness as Construction of Open Identity: How Social Relationships Affect Attitudes Towards Immigrants in European Societies

Abstract

Studies of individual and group-level sources of prejudice have contributed to today’s greater understanding of the emergence of prejudice and discriminatory attitudes towards immigrants. Yet, scholars have claimed that future research should investigate institutional and socio-political macro-level factors affecting individuals’ attitudes towards outsiders (Ceobanu and Escandell in Ann Rev Sociol 36:309–328, 2010). To contribute to filling this knowledge gap, this article goes across levels of analysis and theories to provide insights about group-level sources influencing attitudes towards immigrants. These sources are taken into account as both institutional and social factors involved in processes of national identity constructions. To this purpose, this work combines Blumer’s perspective (Pac Sociol Rev 1:3–7, 1958) with both the distinction Weber (Wirtschaft und Gesellschaft. Tübingen, Mohr, 1922) made between open and closed social relationships and some other theoretical contributions that emerged in the field. The findings of a multilevel analysis confirm that, whereby inclusive socio-political factors are involved in the processes of countries’ identity constructions, individuals show more positive attitudes towards immigrants. In addition, in inclusive countries, a society’s high regard for its own traditions and customs influences individual members to appreciate other cultures and show positive dispositions towards outsiders.

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Notes

  1. 1.

    According to European statistics, the total number of long-term immigrants has always increased since the mid-1970s, with a slight decrease in 2011 only. See Eurostat database topic “Immigration” code tps 00176. <http://epp.eurostat.ec.europa.eu> (last retrieved 24 February, 2014).

  2. 2.

    Respectively, “communitarization process” and “socialization process”. Please, see note 4 for a detailed discussion about the translation of these terms.

  3. 3.

    The samples come from the database of the European Social Survey (ESS) and the Migrant Integration Policy Index (MIPEX) project. The MIPEX project measures integration policies in the 27 European Union Member States plus Canada, Australia, Japan, Norway, Switzerland and the USA. For further details, please visit the website <http://www.mipex.eu> (last retrieved 24 February, 2014). The European Social Survey database is available at <http://www.europeansocialsurvey.org> (last retrieved 24 February, 2014). Not all the countries participated in both rounds of either the ESS survey or the MIPEX project considered by this study. Countries selected are those for which data are available for both ESS data rounds 4 and 5 and the MIPEX project data for 2007 and 2010. Due to this, 22 countries were included in the index for the year 2008 and 18 countries for the year 2010, for a total 40 cases at the highest level of analysis.

  4. 4.

    This is also frequently connected with the issue of social and collective identities in the more generic sociological debate (Jenkins 1996).

  5. 5.

    In the English translation of Weber’s work, I have found different terminologies instead of communitarian and societal, which are those I propose. In fact, in the English translation we read:

    A social relation will be called “communal” (Vergeimenschaftung) if and so far as the orientation of social action is based on a subjective feeling of the parties, whether affectual or traditional, that they belong together. A social relationship will be called “associative” (Vergesellschaftung) if and insofar the orientation of social action within it rests on a rationally motivated adjustment of interests or a similarly motivated agreement, whether the basis of rational judgement be absolute values or reasons of expediency. (Weber 1922: 40–41)

    However, this is not in line with the German terminology used by Weber, as Vergemeinschaftung means “communitarization process” and Vergesellschaftung means “socialization process”. The English translation disconnects these definitions from the developments made in the field of sociology on socialization process and social identity. Therefore, I propose to use the adjectives “communitarian” rather than “communal” and “societal” rather than “associative”

  6. 6.

    I will substitute the term racial with “inter-cultural”, because, even if race is still an important factor around questions of prejudice, indeed today cultural elements play a major role, particularly in Europe

  7. 7.

    Please, see note 4 for a detailed explanation of the different use of terminology I have employed.

  8. 8.

    For details, please see the ESS website http://www.europeansocialsurvey.org (last retrieved 24 February, 2014).

  9. 9.

    For additional information, please refer to the MIPEX project website www.mipex.eu (last retrieved 24 February, 2014).

  10. 10.

    See details on the website http://stats.oecd.org (last accessed 24 February, 2014).

  11. 11.

    Indices are usually preferred to single items as dependent variables, because they avoid the problem of equivocated replies. In order to verify my findings more robustly, I also tested the models on the index made up of three items on ATI. The findings obtained are similar to those obtained on the single item. Because of length issues, I cannot include here this analysis. The author is happy to share full results upon request.

  12. 12.

    See Ceobanu and Escandell (2010) for a detailed discussion of this issue.

  13. 13.

    I chose to employ a Box-Cox transformation instead of traditional transformations (square root, cubic root, log, inverse, etc.) because a number of studies have demonstrated that the Box-Cox transformation (Box and Cox 1964) represents best practice when normalizing data, as it extends and improves the traditional family of power transformations (Osborne 2010).

  14. 14.

    As previous multilevel analysis using the ESS dataset (Davidov et al. 2008), the following ESS items included in a composite measure were used to test the alienation theory:

    • “you can’t be too careful or most of the time people can be trusted” (scale 0–10);

    • “most people try to take advantage of you or most people try to be fair” (scale 0–10);

    • “most of the time people are helpful or mostly people are looking out for themselves” (scale 0–10).

    The three items were recoded so that the higher the score, the more alienated the individuals. The three items are summed into a single component (KMO adequacy = .693; Bartlett’s test significant; eigenvalue = 2.064 explaining 69 % of the total variance. Cronbach’s alpha = .772).

  15. 15.

    This variable had non-normal value of kurtosis; thus it was recoded in 4 categories, following the same order suggested in the ISCO88 classification: from the lowest to the highest skilled occupation (0 = non-skilled; 1 = skilled; 2 = highly skilled; 3 = elite).

  16. 16.

    In order to facilitate interpretation, the item was recoded from “less” to “more comfortably living with present income”.

  17. 17.

    The question of this item is “Regardless of whether you belong to a particular religion, how religious would you say you are?”.

  18. 18.

    This second item was originally coded using a scale from 1 = “every day” to 7 = “never”. In order to facilitate interpretation, I inverted the codes.

  19. 19.

    I use the item “it is important to follow traditions and customs handed down by religion or family” (scale: 0–6).

  20. 20.

    Despite this, the autor has also run a multilevel analysis without the varaible conservatism, which substantially shows the same results then the analysis provided in this article. The author is pleased to share these results upon request.

  21. 21.

    See details on the website http://stats.oecd.org (last retrieved 24 February, 2014).

  22. 22.

    In this model, I do not include any variable on origins of immigrants due to a lack of data for most of countries. This problem persists both when using data on immigrant population percentages from the Eurostat database and using those from the OECD database. See details on the website http://ec.europa.eu/eurostat (last accessed 24 February, 2014).

  23. 23.

    The minimum acceptable value is .60; values higher than .90 are optimum.

  24. 24.

    In general, the maximum likelihood method is the more robust. Its restricted application is preferable to full application because REML has less bias. Furthermore, when group sizes are balanced, like in my sample, the REML estimates correspond to those obtained with ANOVA estimates, which are optimal (Hox 2010: 40–47).

  25. 25.

    This means that, when taking into account the effect of a variable, we are considering an average case presenting all the other variables as fixed at the mean of the whole sample (at the European level in my sample). This is necessary because otherwise the multi-level technique calculates estimates net of other variables fixed at zero, and zero is sometimes not a possible value on the scale of some of the variables employed in the model. The grand mean centring method is the best solution; it does not remove group differences, as centring around the group mean would do (Hox 2010: 64 ss.). The other possibility would have been to standardize the variables, but “In multilevel m0deling, centering the explanatory variables has the additional advantage that variances of the intercepts and the slopes now have a clear interpretations… Since grand mean centering only affects the intercept, which is often not interpreted anyway, it is preferred above standardization, which will also affect the interpretation of the regression slopes and the residual variances” (Hox 2010: 51; 52–53).

  26. 26.

    Tables for these additional analyses are not included. However, the author is happy to provide them upon request.

  27. 27.

    National data on immigrants’ origins are only available only for 15 countries (in 2008 and 2010) in the OECD statistics. This did not allow to employ a multi-level analysis, particularly as the Intra-class correlation is too small (.06).

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Acknowledgments

I wish to thank Juan Diez Medrano, for his comments and support throughout the research project, Bart Meuleman, for his feedback on multi-level analysis, and to Matthias Von Haum, Fulya Apadyurin, Anna Herranz and Yannis Karagiannis for their comments on my work. Especially, I thank my colleague Tendayi Bloom and the anonymous reviewers for their insightful comments and suggestions.

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Bello, V. Inclusiveness as Construction of Open Identity: How Social Relationships Affect Attitudes Towards Immigrants in European Societies. Soc Indic Res 126, 199–223 (2016). https://doi.org/10.1007/s11205-015-0881-1

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Keywords

  • Immigrants
  • Attitudes
  • Inclusiveness
  • Social relationships
  • Socio-political factors
  • Prejudice