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In this section, hypothesis 4.1, 5.1 and 6.1 will be presented and tested with the use of partial regression analyses. The results of these analyses can be found in table 10 where all variables are entered as discussed in the previous sections. The first assumption, based on the theoretical framework in chapter 1, is that the social climate in a neighborhood will be influenced by the distance. If we take a look at column M1 in table 10, it is clear that the distance and the level of social cohesion are positively related to each other on a significance level of 0.00 and an adjusted R2 of 0.24. This means that the level of social cohesion is influenced by the distance for 24% if no other variables are involved. With this result hypothesis 4.1 can be confirmed, because if the distance will increase the level of social cohesion in a neighborhood will rise.

Table 10: Partial regression analyses between the distance, the physical characteristics, the social composition and the level of social cohesion

If we look at the theoretical framework in chapter 1, it is plausible that the distance influence the level of social cohesion in a neighborhood. In this framework, the assumption is presented that citizens who live near the city center in social rental apartments, have the least social cohesion outside their housing blocks or streets. This because these citizens are strongly focused inward with respect to their social contacts and their contacts with other ethnical groups is seldom (Van Stokkom and Toenders, 2010). This assumption seems to be underwritten by the statistical results, but this statement also suggests that the value of the dwellings and the percentage of non-vacant dwellings – which are low in zone 2 - will influence the level of social cohesion. Hypothesis 5.1, as formulated above, will test this relation.

Column M2 in table 10 show the partial regression analyses between the distance, the physical characteristics and the level of social cohesion. The distance, as discussed before, still influence the social cohesion in a positive significant manner, but the coefficient is decreased from 0.50 to 0.33. This means that the influence of the distance is also present via other variables. If we include the physical characteristics in the model it is clear that the value of the dwellings plays an important role that also explains the decrease of the influence of distance. The value of the dwellings in this case is the intervening variable. The percentage of the non-vacant dwellings is also positively related to the level of social cohesion, but this relation is not significant. In other words, the distance does influence the social cohesion in a direct way, but also in an indirect way via the value of the dwellings. The adjusted R2 is 0.38, which means that the social cohesion is influenced for 38% by the distance and the physical characteristics.

M1 M2 M3 Exp. Distance 0.50 0.00 0.33 0.00 0.31 0.00

+

Physical characteristic 1 Value of dwellings 0.40

0.00

0.15

0.16

+

Physical characteristic 2 Non-vacant dwellings 0.10

0.26

0.06

0.47

+

Social composition 1 Dutch native citizens 0.40

0.00

+

Social composition 2 Residential stability 0.10

0.26

+

R2 0.25 0.41 0.52

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If we take a look back at the theoretical framework, the general assumption is that the level of social cohesion is higher in neighborhood where citizens live in high valued houses. The percentage of the non-vacant dwellings, as shown in table 10, is not significant related to the level of social cohesion.

If we take a look at the theoretical framework, this result is not surprising. The assumption is that in areas where cheap (social rental) houses are located, neighbors produce little new information (Power and Willmot, 2007). Of course citizens talk to each other more often than citizens in highly secured neighborhoods but the lack of new information ensures social fragmentation what discourage contact with other citizens. Based on this information it is clear that hypothesis 5.1 cannot be confirmed completely, because only the value of the dwellings influences the level of social cohesion. The percentage of the non-vacant dwellings is not statistically significant.

Next to the distance and the physical characteristics, it is assumable that the social composition – the percentage of Dutch native citizens and the residential stability – can influence the level of social cohesion. The assumption is that neighborhoods with a high percentage of Dutch native citizens and a high residential stability have a high social cohesion. This assumption is presented and will be tested within hypothesis 6.1 which is formulated above. The relation between the social composition and the social cohesion is also presented in table 10 (Column M3). In this table it is clear that the influence of the distance decreases when more variables are entered. More surprisingly, however, is the decrease of the influence of the value of the dwellings and the strong influence of the percentage of Dutch native citizens on the social cohesion. However, it is not ‘strange’ that this relation is high, because neighborhoods with a high percentage of Dutch native citizens have more social contacts with each other and with the neighborhood. This is also discussed in the theoretical framework where Van Kempen (2008) argues that in neighborhoods were citizens live with the same ethnical background, the citizens are more willing to communicate with each other and perform (social) activities together. The residential stability, the other component of the social composition, is not statistically related to the level of social cohesion. This means that only the percentage of the Dutch native citizens will influence the level of social cohesion, so hypothesis 6.1 can only be confirmed partially.

In the table 10 it is clear that all variables together influence the social cohesion for 49% (adjusted R2 of 0.49) but not all the presented relations are statistically significant. In the figure below, all significant relations are presented. In this figure there is a direct effect of distance on the level of social cohesion. Next to this direct effect, there are also two indirect effects. The distance also influences the social cohesion via the value of the dwellings and via the percentage of the Dutch native citizens. This means that the distance influence the social cohesion via three different significant paths.

Figure 13: Significant relations between the distance and the social cohesion

In this section the hypotheses 4.1, 5.1 and 6.1 are presented and tested with respect to the level of social cohesion in a neighborhood. In the next section, the hypothesis 4.2, 5.2 and 6.2 will be presented with respect to the level of participation, the other component of the social climate. The hypotheses 4.2, 5.2 and 6.2 are already presented at the beginning of section 5.3.1.

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