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The Structure of Political Divisions Among American Jews


This paper examines the current structural basis of political divisions among American Jews. Theoretically, the paper is situated in the well-established scholarly tradition of understanding political behavior as rooted in social structural location, with accompanying variations in political cohesion and political division across social groups. Empirically, the paper utilizes data from the Pew Research Center’s 2013 Survey of US Jews to measure and analyze how social divisions based on religion, immigrant status, age, education, income, gender, marital status, region and race are translated into political divisions with respect to both US and Israeli politics. The findings show that religious divisions among American Jews yield the most significant and consistent political divisions across the US and Israeli political measures. Other social cleavages among American Jews also produce political divisions, but to a smaller and less consistent extent than religion.

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  1. 1.

    See also Manza and Brooks (1999).

  2. 2.

    The National Jewish Population Survey 1990 was commissioned by the Council of Jewish Federations (now called The Jewish Federations of North America). The study’s principal investigators were Barry A. Kosmin, Sidney Goldstein, Joseph Waksberg, Nava Lerer, Ariela Keysar, and Jeffrey Scheckner. The data file and supporting documentation are available at the Berman Jewish DataBank at

  3. 3.

    Kotler-Berkowitz (2002) was not limited to an analysis of American Jews; it also included comparative analyses of British and South African Jews, in both those cases also using data from the 1990s and in both cases also finding religion to be the most significant structural source of party divisions.

  4. 4.

    The Pew Research Center ( is a non-partisan fact tank that informs the public about the issues, attitudes and trends shaping America and the world, and as such it does not take policy positions.  The Center bears no responsibility for the analysis, interpretations or conclusions presented in this paper.

  5. 5.

    A multitude of methodological differences between the 1990 National Jewish Population Survey and the 2013 Pew Research Center Survey of US Jews – from sampling to field administration, question wording and order, and estimation and weighting – makes it impossible to directly compare statistical results across them. However, overall patterns, for example, whether religion remains the primary source of political divisions, can be reasonably compared across them.

  6. 6.

    In addition, personal correspondence with Clem Brooks, Professor of Sociology, Indiana University.

  7. 7.

    In my previous analysis (Kotler-Berkowitz 2002), I did not examine the potential political division between in-married and intermarried Jews, but I examine that social cleavage here.

  8. 8.

  9. 9.

  10. 10.

    The Pew study also included two other groups, which the Pew researchers called people of Jewish background and people of Jewish affinity. See the Pew report for details. Neither group is included in this analysis.

  11. 11.

    The reference category and coefficients that are not significantly different from the reference category at p < .05 are set to zero in calculating the mean of the model set of coefficients.

  12. 12.

    For example, a hypothetical set of model coefficients for three categorical variables of .05, −.12 and .23 would, in conjunction with the reference category, have a mean of .04 [(.05 − .12 + .23 + 0)/4 = .04]. The resulting centered coefficients would then be, respectively, .01, −.16, .19 and −.04. The sum and mean of the newly centered (or normalized) coefficients are zero.

  13. 13.

    For example, the indicator of Jewish denomination has five categories. If the categories were evenly distributed, each would contain 20% of the population. But the categories are not evenly distributed. Orthodox Jews are 10% of the population, producing a weight of .5 for them (.1/.2 = .5). Reform Jews are nearly 36% of the population, producing a weight of 1.79 (.358/.2 = 1.79).

  14. 14.

    Kappa could be calculated using the bivariate cross-tabulations of social divisions and political measures, but using coefficients from regression models allows kappa to be calculated for each social division net of the effects of other social divisions.

  15. 15.

    In addition, personal correspondence with Clem Brooks, Professor of Sociology, Indiana University.

  16. 16.

    For example, a hypothetical set of kappas of .30, .18, .05 and .01 would be scaled to 1, .60, .17, and .03.

  17. 17.

    See the Appendix for an alternative approach to the regression models and calculation of kappa.

  18. 18.

    Relative to religion, the average strength of the political divisions produced by education is .37, age is .44 and gender is .28.

  19. 19.

    Relative to religion, the average strength of the political divisions produced by immigrant status is .47, race is .44, marital status is .39, income is .39 and region is .22.

  20. 20.

    Marital status and income come very close to producing the same level of political division as religion on government size and services.

  21. 21. Accessed 10 July 2015.

  22. 22. Accessed 10 July 2015.

  23. 23.

    They are not scaled because they are already all on the same metric, namely 0–100%.

  24. 24.

    This kappa, .12, should not be compared to the scaled kappa, 1.00, for party support in Table 6.

  25. 25.

    The fact that the kappas for Americans generally are based on voting, rather than party identification, may increase their size somewhat because voters tend to return more strongly to their parties at elections than off-election year measures of party identification may indicate. As a result, the difference between kappas for Americans generally and the kappa for US Jews may be slightly smaller than indicated.

  26. 26.

    It is possible that measures of Israeli politics unrelated to the Israeli-Palestinian conflict, were they available, might not be structured as strongly by religious divisions.

  27. 27.

    It is well known that disentangling cohort and life-cycle effects with cross-sectional data is extremely difficult. The debate over cohort vs. life cycle effects also animates the research on emotional connections to Israel, and to date there is no consensus in the scholarly literature on the issue (Cohen and Kelman 2010; Kotler-Berkowitz and Ament 2010; Sasson et al. 2010).

  28. 28.

    Recoding varied. For party identification and ideology, two categories were combined and predicted against the other categories combined. For government size/services and two-state solution, the modal category was predicted against all other categories combined. For US support of Israel and settlements, the modal category was predicted separately against each other category. See footnotes in Tables 9 and 10 for details.

  29. 29.

    The average kappa for religion across the 11 measures is .57, followed in order by age (.33), immigrant status and race (.27 each), education (.25), income (.19), gender and marital status (.18 each), and region (.11). Averages not displayed in tables.

  30. 30.

    Though religion structures Obama’s job approval more weakly than it does all other dependent measures except for one, it still structures Obama’s job approval more strongly than all the other predictors do.


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Empirical findings from this analysis were first presented at a session on American Jewish politics at the 46th Annual Conference of the Association of Jewish Studies, December 14, 2014, Baltimore, MD. I thank Larry Sternberg, Steven M. Cohen and three anonymous reviewers for their critical review and helpful comments on earlier versions of the paper, and Clem Brooks for guidance on methodological issues. I alone retain responsibility for the analysis and interpretation presented here.

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Correspondence to Laurence Kotler-Berkowitz.



In the main analysis, initial kappa was calculated by centering and weighting regression coefficients, and final kappa was calculated by transforming initial kappa to a 0–1 scale. This was done because the regression coefficients were generated using 1) dependent variables with different metrics and 2) different regression techniques. The final kappas show the relative magnitude of political divisions structured by social cleavages within dependent measures, with the largest initial kappa scaled to a final kappa value of 1 and all other initial kappas scaled to a proportion of the largest final kappa. As a result, patterns of relative magnitude across the dependent measures can be examined, but the values of the final kappas cannot be directly compared to each other across dependent measures. In other words, on all measures where religion has a final kappa of 1, it signifies that religion structures the most significant political division on that measure. However, it does not mean that religion structures political division to the same extent across the measures.

In order to compare kappas directly with each other, they need to be calculated from regression coefficients that are generated using 1) dependent variables that have the same metric and 2) the same regression technique. That approach is taken here by recoding the six ordered dependent measures into eight dichotomous variables,Footnote 28 keeping the three original dichotomous variables as is, and using binary logistic regression to predict all 11 variables. Kappas were then calculated by centering and weighting the model regression coefficients, while foregoing the final scaling step. In some cases, recoding the ordinal dependent measures into dichotomous variables results in a loss of a small amount of information, but as compensation the kappas for social cleavages, displayed in Tables 9 and 10, can be compared directly to each other across the dependent measures.

Table 9 US political measures: kappas (centered and weighted) for social divisions
Table 10 Israeli political measures: kappas (centered and weighted) for social divisions

The patterns are consistent with the main analysis. Religion, as measured by denomination, generates the most significant political divisions on eight of the 11 measures, produces the highest average kappa across the 11 measures,Footnote 29 and in no case fails to produce political divisions. Calculating kappa this way shows that religion structures the most significant political division with respect to societal acceptance or discouragement of homosexuality, followed by US support for Israel when the trade-off is about the right support vs. too supportive, and settlements when the trade-off is settlements hurt Israeli security vs. settlements help Israeli security. Religion yields the least significant political divisions on government size and services and Obama’s job approval.Footnote 30

When religion is not the primary source of political division, it is replaced by education and gender on government size and services, age on the Israeli government’s peace efforts, and race on settlements when the trade-off is settlements hurt Israeli security vs. settlements make no difference to Israeli security. In each of these cases, religion generates political divisions only moderately weaker than the top social divisions, and in none of those cases do the alternative social divisions produce the same level of political division that religion does when it is most potent.

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Kotler-Berkowitz, L. The Structure of Political Divisions Among American Jews. Cont Jewry 37, 5–27 (2017).

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  • Social divisions
  • Political divisions
  • American Jews
  • Religion