The preceding analysis is interim in nature and leaves much room for improvement, not least in terms of specification of the variables included in the models. Still, if the variables used are accepted as rough indicators of the concepts that are at play then some initial observations can be made. First amongst these is that the Civic Voluntarism Model does a good job of accounting for the frequency of political activity, and performs better in this regard than the Bourdieusian and perceptual model. Those components do add a small amount of power to the Civic Voluntarism Model, when included in the full model, but they leave a lot to be desired from the perspective of parsimony.
Much of the power of the Civic Voluntarism Model stems from the inclusion of the group recruitment variable, which is by far the most powerful predictor of political activity in the full model. Questions remain around the proximity of the question underpinning this variable to the dependent variable in the original survey but, assuming that it is not compromised, it is clear that Verba, Schlozman, and Brady were right to identify it as a component of their model. In fact, the strength of its relationship with the dependent variable suggests that it may be worth running separate analyses in which recruitment is treated as the dependent variable. Further, if recruitment is such a strong predictor, it may be worth investigating whether there are other different processes at play across groups that are frequently or infrequently recruited, for instance by comparing separate analyses across those groups.
If the performance of the Civic Voluntarism Model, and recruitment in particular, is difficult to ignore this should not lead us to overlook the consistently active variables in all four elements of the full model. These robustly significant relationships indicate further interesting results that may need to be teased out through more complex analyses. Such analyses should focus first on specifying improved variables, based on the available survey questions, through confirmatory factor analysis. Such variables could then be utilised in structural equation modelling that has the capacity to accommodate a more complex structure of relationships between variables than does multiple regression. These are the next steps for the current research.
Until those analyses are undertaken, however, we can take away some interim observations about particular variables from the current analysis. First, identifying as non-heterosexual, considering oneself to be limited by a disability, and having health conditions are all associated with greater political activity. Second, exercising key civic skills at work, being interested in politics and discussing it, and being asked to get involved in voluntary groups are all positively related to political activity. Further, interest in politics and group recruitment are two of the strongest predictors of political activity. Third, having an array of cultural tastes is negatively associated with political activity but being culturally active is positively associated. By contrast, having a range of social acquaintances is positively associated with political activity. Fourth and finally, perceiving the role of privilege in structuring society is positively related to political activity. Thus, whilst Verba, Schlozman, and Brady’s Civic Voluntarism Model does an impressive job of explaining political activity, it seems that parts of the Bourdieusian and perceptual model also have a part to play.