In Part 1, we introduced the concept of social capital, which refers to connections between people that generate trust, norms of reciprocity, and participation in civic life. In general, people that join groups and interact regularly in social networks are cooperative, obliging, and inclined to do things for others.
We suggested this community-mindedness would be well suited for effective social distancing. After all, a key motivation for distancing is the health of our communities including, friends, neighbors, and vulnerable others.
The descriptive data presented did show that Kansas counties high in social capital received substantially better social distancing grades than low social capital counties.
We now scrutinize the relationship with a statistical model that isolates the effects of voter turnout from other variables expected to influence distancing – such as county population, income, percent minority, percent health insurance, and confirmed number of Covid-19 cases.
The Table below lists only statistically significant variables. Grades are derived from model forecasts that return the estimated impact of each predictor – holding other variables at typical levels.
For example, the model predicts a C+ for the least populated county and a D for the most populated. In sum, smaller population counties post higher grades than larger ones.
Similarly, the poorest county realized a better grade C+ that the wealthiest C-.
Why would affluent counties grade lower than poorer ones? After all, many well paid professions can work remotely and the wealthy can “afford” an extended lockdown. Without more detail, and individual-level data, we can only speculate.
Model estimates of key predictors of social distancing grades
In addition, counties with sizeable minority populations performed better than counties with less minorities – moving from a grade of C to a B -.
While the national statistics, and figures in certain states including Kansas, show minorities account for a disproportionate share of Covid-19 infections and deaths, this does not imply a failure to distance. Rather, in Kansas counties where minority populations are significant, social distancing grades are better than where minorities are absent.
Finally, our measure of social capital – voter turnout – produced the largest impact on distancing. The model returned a social distancing score of D + for the lowest turnout county. And for the highest in turnout, the grade advanced a full letter and then some to a B -.
Would millions of Americans adhere to social distancing guidelines? This question lingered as elected officials authorized lockdowns across the nation. The Kansas data suggests observance varied, and substantially so. Many Kansans did obey the guidelines, and the county grades show substantial reductions in mobility and human interaction. However, many counties received average to failing grades.
The counties that tended to score higher, and thus comply with distancing guidelines, possessed notable stocks of social capital – high voter turnout.
Social capital nurtures civic engagement which is a means to address public concerns and protect community values. For many, voting is an obligation and a responsibility to fellow citizens and to government. The regard for community and a tangible cooperative spirt presents an ideal environment for successful social distancing.
Critics however may counter that compliance turns on fear of grave illness and death – motives centered on self, not on community nor vulnerable others.
Yet if self-interest sent people inside their homes, why did counties reporting no infections comply so successfully? Some even achieved the highest grades. For example, 29 Kansas counties did not report a single Covid-19 infection. The average distancing grades among them was a B -, 6 scoring B’s and 3 at an A-.
Fear surely increased in counties reporting substantial outbreaks and deaths. But it did not seem to translate into an effective reduction in activity. In many counties that suffered unusually high outbreaks, compliance remained modest to poor. In fact, the number of confirmed Covid-19 cases did not influence social distancing grades.[i]
Finally, nearly two decades ago Putnam cautioned about the decline of social capital. The pandemic underscores his warning and draws attention to the quality of our social fabric. Among the variables examined, only social capital can be developed and renewed. A healthy public might actually depend as much on a vigorous collective spirt as on medical advancement.
[i] As expected, Covid-19 infections are strongly correlated with population (r = 0.71). If we remove population from the model, Covid-19 infections reach statistical significance showing a negative association with social distancing. In other words, counties that report low infection rates receive better grades than counties with more infections. However, population must be considered in the model. In addition, Covid-19 as a proportion of population does not affect social distancing.