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Civic Activism as a Novel Component of Armenian Civil Society

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eport higher levels <strong>of</strong> trust in online media 17 and social networks 18 and are more frequent users<br />

<strong>of</strong> social networking cites <strong>as</strong> a source <strong>of</strong> information about current events and news. 19<br />

Settlement type: The majority <strong>of</strong> people in Yerevan (58%) report having used the<br />

Internet in the p<strong>as</strong>t 12 months, while this is not the c<strong>as</strong>e in other urban settlements and rural<br />

are<strong>as</strong>, where 45% and 36% <strong>of</strong> respondents reported doing so, respectively. The difference is<br />

statistically significant. 20 People in Yerevan are less trustful <strong>of</strong> online media and social networks,<br />

compared to residents <strong>of</strong> rural are<strong>as</strong>, 21 although they use social networking cites more frequently<br />

to obtain information about current events and news. 22<br />

4.2.2. Actual and Potential Activists<br />

<strong>Civic</strong> initiatives need popular support. If activists want to attract more people to their cause, it is<br />

logical to target people that are more inclined towards taking political action. We use WVS data<br />

on four types <strong>of</strong> non-conventional political participation, discussed above (petitions, boycotts,<br />

demonstrations and strikes), <strong>as</strong> me<strong>as</strong>urements <strong>of</strong> political activism. To simplify the analysis, we<br />

recalculated the original variables into new dummy variables, combining the “have done” and<br />

“might do” response categories, thus creating a simple dichotomy between people who said they<br />

would never engage in the type <strong>of</strong> political activity mentioned and those who are willing to or<br />

have already done so.<br />

We examine each <strong>of</strong> the four types <strong>of</strong> political actions, <strong>as</strong>sessing whether age, gender,<br />

education and income influence the likelihood <strong>of</strong> participation. We also note whether the picture<br />

in 2011 is different from that in 1997. Table 2 below summarises the results <strong>of</strong> t-test and chisquare<br />

analysis. Only statistically significant results are reported.<br />

16 T-test: t(1373) = 14.289, p < 0.001 for year 2013.<br />

17 Pearson’s r = 0.212, N = 661, p < 0.001 for year 2013.<br />

18 Pearson’s r = 0.163, N = 629, p < 0.001 for year 2013.<br />

19 Pearson’s correlation: r = -0.364, N = 1359, p < 0.001 for year 2013.<br />

20 Chi-Square: X 2 = 46.946, df = 2, p < 0.001 for year 2013.<br />

21 ANOVA: F(2, 675) =3.684, p < 0.05 for online media variable and F(2, 645) =3.906, p < 0.05 for the social<br />

network variable for the year 2013.<br />

22 ANOVA: F(2, 1381) =19.400, p < 0.001 for year 2013.<br />

30

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