The Green Line and the Security Fence:

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14 one of these qualities. 22 Still, it is a relief to know that our data both qualitatively (the sign of regression coefficients) and quantitatively (their high significance) support conclusions made by Shamir and Arian (1999), Shalev and Kis (2002), and Andersen and Yaish (2003) about the major trio (ethnicity, religiosity, nationality) + social factor, while pointing to several interesting clarifications at the same time. This, in turn, justifies our correct choice of the control parameters in our major research directed to mathematically represent the psychological (security) issue. 23 3. Regarding Ethnic Background, we chose the smallest possible set of representatives: either entire continents: Asia, Africa, North and South America, and Europe – or the countries that represent their political preferences most prominently. True, several countries, like Turkey, Romania, and Bulgaria, defy this simplified description, but they do not influence much the results and after all we need this variable only as a control. 4. The question about religiosity does not exist in the census, and this is its major deficiency regarding our analysis. We had to invent a plausible variable to represent it: large families (7 or more members) could represent the religious group while single people are more likely to be non-religious. This choice is justified a posteriori, since the former group votes strongly Right while the latter group votes strongly anti-Right. 5. Though all variables, including dependent ones, are qualitative, except Income, after aggregation they became “quantitative,” which makes the technical analysis much easier. Therefore, to analyze census aggregate data, we chose linear regression instead of logistic
15 regression, since the sign and significance of linear regression coefficients allow for direct interpretation. 6. There is a raging debate on exactly what “class” is. Andersen and Yaish (2003) argued that “class” is defined solely by individual (family) income and occupation. Shalev and Kis (2002) added to this pair the “population density.” We took the side of Andersen and Yaish so as not to compute an extra parameter. As a proxy for “occupation” we used “academic degree.” Though usually considered as “education,” an academic degree also reflects “class” status within Israeli society. 7. In the study of P-factor, it would be too costly to discard the electoral areas with a partial Jewish population, say, with 5-10% of Arabs. However, in such areas the figures of the vote will not give adequate figures for Jewish voters we are seeking. Indeed, the individual poll shows that the Arabs vote overwhelmingly Left. Such areas with 5-10% Arab populations are pretty numerous in Jerusalem and Haifa. Therefore, we introduced a correction coefficient for the dependent variable (vote for the Right): K = 100% / (100% - % of Arab votes) which is adequate for the low percentage of Arab voters. Indeed, in the area with 10% percent Arabs, the result of a 50% vote for the Right must be interpreted as 55% of Jews voted Right – which is adequately represented by K=10/9 = 1.1. 8. To eliminate locations beyond the GL appeared to be an inevitable decision, since it is unclear how to measure them properly. The “minus” sign was considered as an option, but was not a successful one. For example, the city of Ariel is located in the center of the
Page 1 and 2: The Green Line and the Security Fen
Page 3 and 4: 3 increase in the importance of the
Page 5 and 6: 5 Goemans 2001), 2 the two-ballot s
Page 7 and 8: 7 Jewish Israeli population) forced
Page 9 and 10: 9 Since the 1993 Oslo Accords, the
Page 11 and 12: 11 the Meretz Party, which was a pa
Page 13: 13 1. The first issue is that the c
Page 17 and 18: 17 made up of small communities. In
Page 19 and 20: 19 Israeli population was divided i
Page 21 and 22: 21 80% 60% 40% Each city is represe
Page 23 and 24: 23 the fifth level. After adding so
Page 25 and 26: 25 At the fifth level there were ad
Page 27 and 28: 27 Analysis of the Results The fact
Page 29 and 30: 29 while statistical data from the
Page 31 and 32: 31 goodness of fit - the best is to
Page 33 and 34: 33 Category Variables B S.E. Wald S
Page 35 and 36: 35 1. The aggregate data analysis s
Page 37 and 38: 37 to vote Right in Tel Aviv (20 km
Page 39 and 40: 39 1 This is the old approach in Is
Page 41 and 42: 41 Masters degrees. We refer to the

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