Abstract
Increasing interest in the political consequences of exposure to politically divergent viewpoints has revealed contrary findings. Although there is reason to believe that politically diverse networks should mobilize people into participation, some research finds inhibiting or negative effects on political participation. In recent work, this discrepancy has been explained by different measures of political diversity. In this article, we reconsider these two perspectives and offer a theoretical synthesis of the effects of political diversity by differentiating between individual and collective characteristics of different participatory acts. Drawing on the Canadian Youth Study, we test these assumptions among young people, who are particularly susceptible to peer influence. The results show that young people, who report higher levels of interpersonal political diversity are more likely to be engaged in a variety of political acts performed individually. However, there is no evidence that political diversity negatively affects more collective forms of political action that are based on face-to-face interactions. Thus, it is important to make distinctions between not only different measures of exposure to political diversity or disagreement but also the different nature of political actions that might be affected.
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Notes
In addition to the positive and negative findings, a number of authors have also found no or at least limited effects of political network diversity on political participation (Huckfeldt et al, 2004; Nir, 2005; McClurg, 2006b; see also Teorell, 2003).
Although see Huckfeldt et al (2004). While they find network diversity increases ambivalence, they fail to find an impact of political diversity on electoral participation.
However, the coefficients for the diverse networks variable in the two models were not statistically different from each other, leading to caution in interpreting this difference.
See, for example, Eliasoph (1998, p. 6).
See, for example, work on false consensuses by Krueger and Clement (1994).
We do not mean to imply that there is no relationship between acts performed individually and acts performed collectively. Some people are more likely to be participatory for a host of reasons, including genetic, parental socialization, mobilization and institutional factors, all of which have little impact on the type of act. However, our argument is that there are reasons to expect that the character of social networks is particularly likely to have divergent effects on the type of political action, namely whether it is performed individually or with others.
Despite the fact that they are highly correlated, the intention to participate has been proven to be an overestimation and a poor predictor of actual behavior (Brady, 1999).
For detailed information about the sample design, see Stolle et al, 2006.
The responses on the Political Action scale ranged from 0 to 17, with an average response of 3.2. We have recoded those from 9–17 to 9, in order to achieve a more normal distribution. Models run with the full scale do not change substantively the results (not shown).
The Individual Political Action scale includes wearing a patch, forwarding an email, displaying a political message, buycotting, boycotting and signing a petition. The original 3-point scales were added together, resulting in a final scale from 0–12. The individual political action scale is reliable (Cronbach’s α=0.6532). The collective participation items do not scale together well (Cronbach’s α=0.2288) on a statistical basis, however, they do fall on the same theoretical dimension of involving social coordination and face-to-face activities. As the proceeding analysis shows, we do not find effects for the collective scale. Similarly, analyses run separately by item fail to produce significant effects.
The 7-point scale was labeled: none, almost none, a few, about half, many, almost all, all.
In instances where the respondent only completed one of the two scales, responses to a single scale were imputed to minimize missing values (n=152). Cronbach’s α for the collapsed network scale is 0.67.
It is essential to control for social context because social cleavages in a community largely determine the types of social cleavages found in one’s social circles (Huckfeldt et al, 1995; Campbell, 2006, Ch. 4).
Clustered robust standard errors were estimated using Stata’s cluster command.
This is especially the case given that a lot of fundraising for various causes among youth invariably takes place within the school environment. Civic engagement more generally is often facilitated for young people within the school environment, where service activities can be encouraged, and even required, by the curriculum (Zukin et al, 2006, pp. 144–146).
However, we find no difference between whites and non-whites in the level of political diversity in their social networks.
Model not shown. Available upon request from authors.
This effect holds across the two provinces in the sample, and is robust to alternative controls and alternative estimation strategies, including both poisson and negative binomial estimations (not shown).
An analysis of variance inflation factors reveals that none of the variables have VIF scores of above 1.6.
This is not to say that discussion and exposure to diversity are not related, as they certainly are correlated (r=0.37). But we do find some variation in political diversity even among those who do not discuss politics. Again, as detailed above, discussion is not a requirement for perceiving attitudinal difference (Burnstein and Vinokur, 1975; Goel et al, 2010), as people are capable of picking up cues and making inferences about their friends’ political preferences.
Note, however, that the results are similar when the full 3-point scale is used in ordered logits, with consistently significant results for network diversity on individual acts, and no corresponding effect for collective acts (results not shown).
Full models are available from the authors. Note as well that these results are robust to alternative modeling techniques. Ordered logits using the original full 3-point scale return substantively identical results, with positive, significant coefficients for political diversity for the six individual acts, and null effects for the three collective acts.
These coefficients are statistically different from each other at the 0.10 level. Note that while close and weak ties are correlated (r=0.50), there is no evidence that this collinearity is detrimental to the model in Table 2: variance inflation factors are all variables are below 1.6.
Results not shown.
Note that these results are robust to various specifications of independent variables in the propensity score model, as they are to different matching techniques. Political diversity is consistently positive and significant for individual political action, and the effect for collective action is consistently about a fourth of the size and rarely significant.
Models are identical to previous specifications, with the added inclusion of the interaction term (not shown). The full models are available from the authors.
However, we find no effect on the collective action items. We suspect this is because there is simply no effect of network diversity for such acts.
Name generators ask respondents to provide a short list of specific individuals (often close friends), and then to provide background information on each. This leads to very specific information about diversity, yet tends to provide a small list of primarily very strong ties.
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Harell, A., Stolle, D. & Quintelier, E. Experiencing political diversity: The mobilizing effect among youth. Acta Polit 54, 684–712 (2019). https://doi.org/10.1057/ap.2016.2
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DOI: https://doi.org/10.1057/ap.2016.2