Goal & Concept
Goal
The goal of this exercise is to examine the relationship between demographic characteristics and different forms of civic participation. Crosstabulation will be used.
Concept
Civic participation can be defined as involvement in activities intended to influence public policy and leadership. The most common form of civic participation is voting, but there are several other forms of civic participation as well. Some of these more non-traditional forms of civic participation are volunteering to work for a campaign, donating money to a campaign, and protesting. These forms of civic participation, in addition to voting, give people the opportunity to voice their concerns and opinions regarding candidates or issues. While these non-traditional forms of participation do not directly impact vote totals, they do often gain the attention of the media and of candidates, thus causing a change in candidates' courses of action. In this way, non-traditional civic participation can influences policies and elections.
Demographics and civic participation are very closely linked in political science research. Most research examining the relationship between demographics and voter turnout suggests that, on average, older, higher income, white people have a better turnout rate than other voters. While there has been less research done on demographics and non-traditional civic participation, there is reason to believe that the same type of relationship exists. In the context of this exercise, it is expected that older, wealthier respondents participate more often, on average, than younger, less wealthy respondents.
Research questions regarding non-traditional civic participation and demographics include:
- What is the relationship between certain demographic categories and volunteering for a campaign, contributing money to a campaign, and taking part in a political protest?
- Which forms of non-traditional civic participation are most popular among all groups?
- How do elected officials and candidates respond to non-traditional forms of civic participation?
Dataset
The data for this exercise come from the American Citizen Participation Study, 1990 . The study was designed to examine political and non-political civic participation in the United States. Respondents were asked about their interest in politics, their party identification, their community involvement, as well as their campaign activities, and about their monetary contributions to any campaign. Respondents were also asked to comment on social, political, and economic problems in the United States, and on why people are not more politically involved. Demographic variables in this study include education, occupation, religious background, race, ethnicity, age, gender, and union membership. This study used a clustered and stratified probability sample.
Variables used in this exercise:
- Volunteered for 1988 presidential campaign (CW88)
- Monetary contribution to 1988 presidential campaign (CM88)
- Participated in protest in past two years (PT2YRS)
- Year respondent was born (YEARBORN)
- Respondent's gender (GENDER)
- Family Income (FAMINC)
Application
In this exercise, you will examine the relationship between non-traditional civic participation and demographic characteristics. Crosstabulation will be used.
In this dataset, respondent's age can be measured by subtracting the respondent's year of birth from 1990 (the year the survey was administered). Next, we recoded the age variable into six age groups to make the crosstab analysis more readable. Missing data were excluded as was the individual born in 1978 since all respondents were supposed to be at least 18 years of age in order to be included in the survey. We called the new variable "AGE.CATS." Look at the frequency table for AGE.CATS . Which age group has the most respondents?
Family income was also measured with a large number of categories. We recoded this variable into five income groups (under $25,000; 25,000-49,999; 50,000-74,999; 75,000-99,999; and 100,000+) and named the new variable "FAMINC.CATS." Missing data were excluded from the recode. Look at the frequency table for the new income variable. Which income group has the most respondents? Which income group has the least number of respondents?
Age and Campaign Volunteerism
Now, consider the relationship between age and campaign volunteerism (CW88). Respondents who volunteered for the 1988 presidential campaign were coded as "2." Respondents who did not volunteer for campaign were coded as "1." Examine the crosstab of volunteerism by age. Which age groups are most likely to volunteer?
Gender and Campaign Volunteerism
Now consider the crosstab of campaign volunteerism by gender. What percentage of men in this dataset volunteered to help a campaign effort in 1988? What percentage of women volunteered?
Income and Campaign Volunteerism
Next consider if volunteering for a campaign is related to family income. Are people with higher family incomes more likely to volunteer for a campaign? What percentage of those respondents making less than $25,000 volunteered for the campaign?
Monetary Contributions
It is also interesting to know if contributing money to a campaign varies by age, gender, or income. First, consider the crosstab of 1988 campaign contribution by age group. Which age groups were more likely to give money to a campaign? What does the pattern here tell you about the relationship between these two variables?
Are men or women more likely to contribute money to a campaign? Does this pattern look similar to the pattern in the crosstab between gender and volunteerism?
One would expect those with higher income to be more likely to make monetary contributions to campaigns. Looking at the crosstab of monetary contributions by income, do you observe a pattern that is consistent with this hypothesis? How does this relationship compare to the one between income and propensity to volunteer? Taking the past three crosstabs into consideration, what can you say about demographics and one's propensity to contribute money to a campaign?
Protesting
Consider the relationship between PT2YRS and AGE.CATS. Which age group is most likely to take part in a protest? How does this differ from the other age crosstabs? If there is a difference among these three crosstabs, why might this difference exist?
Are men or women more likely to take part in a protest? Does the relationship between protest participation and gender seem to be different than the relationship between gender and either volunteering for or contributing to campaigns? If so, what is one reason for the difference?
Finally, look at the crosstab showing the relationship between protest participation and family income. Which income group is most likely to have taken part in a protest? Which income group is least likely? Is the pattern here similar to the patterns shown in the other income crosstabs?
Interpretation & Summary
Think about the answers to the application questions before clicking through to the interpretation guide for help in answering them.
Which age group has the most respondents?
Which income group has the most respondents? Which income group has the least number of respondents?
Which age groups are most likely to have volunteered for the 1988 campaign?
What percentage of men in this dataset volunteered to help a campaign effort in 1988? What percentage of women volunteered?
Are people with higher family incomes more likely to volunteer to campaign? What percentage of those respondents making less than $25,000 volunteered for the campaign?
Which age groups were more likely to give money to a campaign? What does the pattern here tell you about the relationship between these two variables?
Are men or women more likely to contribute money to a campaign? Does this pattern look similar to the pattern in the crosstab between gender and volunteerism?
Do you observe a pattern that is consistent with the hypothesis that respondents with higher family income will be more likely to contribute money to a campaign? How does this relationship compare to the one between income and propensity to volunteer? Taking the past three crosstabs into consideration, what can you say about demographics and one's propensity to contribute money to a campaign?
Which age group is most likely to take part in a protest? How does this differ from the other age crosstabs? If there is a difference among these three crosstabs, why might this difference exist?
Are men or women more likely to take part in a protest? Does the relationship between protest and gender seem to be different than the relationship between gender and either volunteering for or contributing to campaigns? If so, what is one reason for the difference?
Which income group is most likely to take part in a protest? Which income group is least likely? Is the pattern here similar to the patterns shown in the other income crosstabs?
Things to think about in interpreting the results:
It is important to look at the amount of missing data in each relationship and think about the ways in which that might affect the generalizability of the results. In general, results from this dataset should be fairly representative of the general population because it is a national probability sample.
Reading the results:
The numbers in each cell of the crosstabulation tables show the percentage of the people who fall into the overlapping categories, followed by the actual number of people that represents in this sample. The coloring in the tables demonstrates how the observed numbers in each cell compares to the expected number if there were no association between the two variables. The accompanying bar and pie charts display the patterns visually as well.
The use of column percentages, as shown in these tables, allows for the comparison of answers to the "outcome" of interest across values of the grouping variable. For example, only 10.2% of those respondents ages 50-59 reported taking part in a protest, compared to 12.4% of those ages 40-49.
Weights (mathematical formulas) are often used to adjust the sample proportions, usually by race, sex, or age, to more closely match those of the general population. The analyses used in this guide did not use any weights, which may reduce the generalizability of the findings, but the resulting tables are accurate descriptions of the relationships found between these variables among these respondents.
The analyses show the following:
More than half (53.4%) of the survey respondents were under age 40 at the time of the survey. 724 respondents (28.3% of the sample) fall into the 30-39 age group. The 70+ age group is the least represented with a total of 173 respondents (6.9% of the sample).
828 respondents (35.8% of the sample) have an annual family income of less than $25,000. This is just slightly more than the number of respondents (822 or 35.6%) whose income is between $25,000 and $49,999. Only 142 respondents (6.1%) claimed to have a family income greater than $100, 000.
Age and Campaign Volunteerism
Respondents age 40-49 were the most likely to have volunteered for the 1988 campaign (24.8%). The next most likely age group to volunteer was 50-59 year olds (20.5%). The youngest respondents were the least likely to volunteer (10.5%).
Gender and Campaign Volunteerism
18% of men volunteered for the campaign, while only 15.6% of women volunteered. If we considered raw number, 212 men said they volunteered for the campaign compared to 208 women.
Income and Campaign Volunteerism
Not surprisingly, higher income is associated with a greater likelihood of volunteerism. The $100,000+ income group is most likely to volunteer (31%), while the under $25, 000 income group is least likely to volunteer for the campaign (8.7%). The percentage of respondents that volunteered for a campaign gets progressively higher as we move from left to right on the bar graph.
Monetary Contributions
Respondents in the 40-49 (43.9%) and 50-59 (43.6%) age groups were the most likely to make a monetary campaign contribution. The youngest respondents were least likely to contribute (14.9%). The pattern suggests that the likelihood of contributing increases with age until about age 60 or so and then the likelihood of contributing declines. This is very similar to the pattern observed between age and volunteering for a campaign except that the likelihood of contributing money is higher than the likelihood of volunteering at all age groups.
Male respondents were more likely than females to make a monetary contribution the 1988 presidential campaign (37.1% to 26.7%). From the table, we note the dark shading in the cells suggests that the observed differences in the sample between men and women in likelihood of campaign contributions is likely to be reflective of a difference between males and females in the population.
Those with the more money are most likely to volunteer and contribute money to a campaign. Respondents who reported over $100,000 in family income were the more likely to make a monetary contribution to the campaign (70.4%). Respondents who reported less than $25,000 in family income were less likely to make a monetary contribution (12.7%). The relationship between campaign contributions and income appears to be even stronger than the relationship between campaign volunteering and income.
Protesting
The youngest respondents are most likely to take part in a protest (15.7%). The oldest respondents (70+) are least likely to take part in a protest (2.9%). In general, the older the respondent, the less likely they are to participate in a protest. The relationship between age and protesting is different than the relationship between age and campaign volunteering or contributing where middle-aged respondents were most likely to volunteer or contribute money. Younger people might be more active in terms of protesting because they may be in better physical shape to protest. They may not have as much disposable income, which may make giving money to the campaign difficult.
Male respondents (12.4%) were slightly more likely than females (11.2%) to have participated in a protest during the previous two years, but this is not a very significant difference. The shading in the cells of the table is relatively light indicating that the relationship is weak. Part of the reason why there is not much of difference between men and women with regard to protesting may be that protesting is not a very common activity in recent years in the United States.
Respondents with a family income of $50,000-$74,999 were the most likely to take part in a protest (16.7%). Those respondents with a family income of less than $25,000 were least likely to take part in a protest (7.1%). This pattern is different from other income crosstabs because in this one, the highest income group is not the most active. However, it is also similar to the other income cross tabs because the lowest income group is still least active (see bar graphs).
Summary
The purpose of this exercise was to examine trends in non-traditional forms of participation across different demographic categories. Generally, the analyses suggest that there are relationships between forms of participation and demographic characteristics, but these relationships are not uniform across characteristics. While the relationships between income and the different forms of participation were consistent, the relationships regarding gender and age were not. Although voting is still the most popular form of civic participation, the non-traditional actions may provide valuable information to elected officials.
Future research might consider how public officials respond to non-traditional forms of participation. Researchers might also consider examining protests in greater depth. A significant portion of political science literature suggests that younger members of the public are less politically active than other members, but our analysis here showed that young people were more likely to become involved in protests. Further research may consider examining more demographic categories (race, education, or possibly region).
Demographics and Non-Traditional Civic Participation: A Data-Driven Learning Guide
Bibliography
We have compiled a list of references (http://www.icpsr.umich.edu/cgi/CITATIONS/search?study={id}&method=study&path=OLC) that might be useful to instructors and students wishing to further explore this topic. All were chosen because they relate to the topic of study, whether or not they use the specific dataset that was used in this exercise. Some relate directly to the concepts as defined by the exercise, others explore the topic more broadly either conceptually or empirically. For even more resources, try a key word search in the ICPSR Bibliography (http://www.icpsr.umich.edu/ICPSR/citations/)!
