Author: Ed Nelson
Department of Sociology M/S SS97
California State University, Fresno
Fresno, CA 93740
Email: ednelson@csufresno.edu
Note to the Instructor: The data set used in this exercise is gss14_subset_for_classes_GENDER_DIFFERENCES.sav which is a subset of the 2014 General Social Survey. Some of the variables in the GSS have been recoded to make them easier to use and some new variables have been created. The data have been weighted according to the instructions from the National Opinion Research Center. This exercise uses RECODE in SPSS to recode some of the variables, FREQUENCIES to get frequency distributions, and CROSSTABS to explore relationships between variables. In CROSSTABS students are asked to use percentages, Chi Square, and an appropriate measure of association. You could skip the part of the exercise that involves recoding since those variables are included in the data set. Then you could go directly to the parts of the exercise that deal with relationships between variables. A good reference on using SPSS is SPSS for Windows Version 23.0 A Basic Tutorial by Linda Fiddler, John Korey, Edward Nelson (Editor), and Elizabeth Nelson. The online version of the book is on the Social Science Research and Instructional Center's website. You have permission to use this exercise and to revise it to fit your needs. Please send a copy of any revision to the author. Included with this exercise (as separate files) are more detailed notes to the instructors, the SPSS syntax necessary to carry out the exercise (SPSS syntax file), and the SPSS output for the exercise (SPSS output file). Please contact the author for additional information.
I’m attaching the following files.
- Data subset (.sav format).
- Extended notes for instructors. MS Word (.docx) format.
- SPSS syntax file (.sps format).
- SPSS output file (.spv format).
- This page in MS Word (.docx) format.
Goals of Exercise
The goal of this exercise is to explore differences between men and women in political attitudes and behavior. The exercise also gives you practice in using several SPSS commands – RECODE, FREQUENCIES, and CROSSTABS.
Part I—Political Attitudes and Behavior
We’re going to use the General Social Survey (GSS) for this exercise. The GSS is a national probability sample of adults in the United States conducted by the National Opinion Research Center. For this exercise we’re going to use a subset of the 2014 GSS survey. Your instructor will tell you how to access this data set which is called gss14_subset_for_classes_GENDER_DIFFERENCES.sav.
Political attitudes and behavior are some of the most widely studied areas in sociology, political science, psychology, economics, and history. To get a sense of the research that has been done go to Google Scholar and enter “political attitudes and behavior” in the search box.
Some of the research has focused on differences by gender, income, education, race, age, and religion. One of the reasons why social scientists are so interested in these individual characteristics is that they serve as markers of a person’s position in the social structure. For example, men and women occupy different positions in the social structure that affect their life chances in such areas as access to quality health care, higher education, and legal representation. This is also true for whites and blacks, older and younger, highly educated and less educated, and so on.
In this exercise we’re going to consider gender differences in political attitudes and behavior. Our data set provides us with a number of different aspects of political attitudes and behavior including:
- political affiliation (P1_PARTYID),
- political orientation (P4_POLVIEWS),
- political interest (P3_POLINT1), and
- voting (P5_PRES08, P6_PRES12, P7_VOTE08, P8_VOTE12).[1]
Part II – Gender Differences in Political Affiliation
Political affiliation or identification refers to the political party with which a person identifies. The GSS uses a series of questions to determine a person’s political affiliation.
- “Generally speaking, do you usually think of yourself as a Republican, Democrat, Independent, or what?”
- Other questions ask how strong a Democrat or Republican a person is and whether independents lean toward the Democrats or toward the Republicans or do not lean either way.
The variable we’re going to use is named P1_PARTYID. Run FREQUENCIES in SPSS to get the frequency distribution for this variable. (See Chapter 4, FREQUENCIES, in the online SPSS book mentioned on page 1 of this exercise.) The categories are strong Democrat (0), not strong Democrat (1), independent, near Democrat (2), independent (3 – i.e., does not lean either way), independent near Republican (4), not strong Republican (5), strong Republican (6), other party (7), don’t know (8), and no answer (9)[2]. The last three values (7, 8, and 9) have already been defined as missing values.[3]
We can use this variable in various ways to describe the political affiliation of the respondents in our sample.
- We could combine the strong and not strong categories and then combine the three values for independents giving us the following categories:
- Democrat (values 0 and 1),
- Independent (values 2, 3, and 4),
- Republican (values 5 and 6).
- We could also combine all those who say they are Democrats and the independents that lean toward the Democrats into one category and then do the same for Republicans. This would leave those who are independent and don’t lean either direction as independents and would give us the following categories:
- Democrat (values 0, 1, and 2),
- Independent (value 3),
- Republican (values 4, 5, and 6).
There are good arguments that can be made for either way of combining categories. We’re going to use the second approach in this exercise. Use RECODE in SPSS to reduce the number of categories using this second approach. When you use RECODE in SPSS, you can recode in two different ways—into the same variable or into different variables. If you recode into the same variable, be careful. It’s easier, but if you make a mistake, you will not be able to go back and recode it again. You will have to close SPSS without saving the data set and then reopen the data set to get a fresh, clean copy of the data. So for this exercise recode into different variables. You’ll have to give your recoded variable a new name. Call this one P1_PARTYID1. (See Chapter 3, Recoding into Different Variables in the online SPSS book.) To make your output more readable, add value labels for this variable.
Compare the unrecoded frequency distribution (P1_PARTYID) with the recoded frequency distribution (P1_PARTYID1) to make sure you recoded correctly. If you made a mistake, redo this part of the exercise. If you recoded into the same variable, you will have to exit SPSS (or close your file) being sure NOT to save it. Then get back into SPSS and open the gss14_subset_for_classes_GENDER_DIFFERENCES.sav file again. The reason for this is that you have altered the coding of these variables and will have to get another copy of the data file to start over. If you saved the data file, then you would have written over the original copy. So be careful. That’s why we said to recode into different variables in this exercise.
Write a paragraph using the recoded frequency distribution to describe how Americans identify with the two major political parties in our country. Use the percents to indicate whether more respondents see themselves as Democrats or as Republicans. How large is the independent category? Keep in mind that these are the respondents who are “true” independents. In other words, they don’t lean either way. How does this category compare in size to that of Democrats and Republicans? What are the implications of these findings for national political elections?
Now we want to compare men and women in terms of their political affiliation so we can look at gender differences. Run CROSSTABS in SPSS to produce a crosstabulation of two variables – D5_SEX and P1_PARTYID1. (See Chapter 5, CROSSTABS, in the online SPSS book.) You’ll need to decide which of these variables you want to use as your independent variable and which you want to use as your dependent variable. The dependent variable is what you are trying to explain and the independent variable is the variable that you think will help you explain the variation in your dependent variable. Put the independent variable in the column and the dependent variable in the row of your table. If you do this, you will always want to tell SPSS to compute the column percents. Also tell SPSS to compute Chi Square, and an appropriate measure of association.
Write a paragraph describing the relationship between the respondent’s sex and political affiliation. Were males more or less likely than females to see themselves as Republican or Democrat or independent? How big was the gender difference for party affiliation? Use the percents, Chi Square, and the measure of association to help you describe this relationship.
Part III – Gender Differences in Political Orientation
Political orientation refers to whether people see themselves as political liberal, moderate (i.e., middle-of-the-road), or politically conservative. The question asked in the GSS is as follows: “We hear a lot of talk these days about liberals and conservatives. I'm going to show you a seven-point scale on which the political views that people might hold are arranged from extremely liberal--point 1--to extremely conservative-- point 7. Where would you place yourself on this scale?” The categories are extremely liberal (1), liberal (2), slightly liberal (3), moderate (4), slightly conservative (5), conservative (6), extremely conservative (7), not applicable (0 – i.e., was not asked), don’t know (8), and no answer (9). The last three values (0, 8, and 9) have already been defined as missing values.
Run FREQUENCIES in SPSS to get a frequency distribution for the variable P4_POLVIEWS. What are the different ways we could recode this variable to reduce the categories to liberal (1), moderate (2), and conservative (3)? Think about whether you want to include those who are slightly liberal and slightly conservative in the moderate category or whether you want to consider them liberal and conservative. How does your decision affect your interpretation of the frequency distribution?
Now use RECODE in SPSS to carry out the recoding that you decided to use. Call the recoded variable P4_POLVIEWS1. Compare the frequency distributions for the unrecoded and recoded variables to make sure you recoded correctly. If you made a mistake, redo this part of the exercise. To make your output more readable, add value labels for this variable.
Now we want to compare men and women in terms of their political orientation so we can look at gender differences. Run CROSSTABS in SPSS to produce a crosstabulation of the two variables – D5_SEX and P4_POLVIEWS1. Think carefully about which variable is your independent variable and which your dependent variable is. Put the independent variable in the column and the dependent variable in the row of your table. Tell SPSS to compute the appropriate percents, Chi Square, and an appropriate measure of association.
Write a paragraph describing the relationship between the respondent’s sex and political orientation. Were males more or less likely than females to see themselves as liberal or conservative or moderate? How big was the gender difference for political orientation? Use the percents, Chi Square, and the measure of association to help you describe this relationship.
Part IV – Gender Differences in Political Interest
Political interest is measured in the GSS by the following question – “How interested would you say you personally are in politics?” The categories are very interested (1), fairly interested (2), not very interested (3), not at all interested (4), not applicable (0 – i.e., wasn’t asked), can’t choose (8), and no answer (9). The last three values (0, 8, and 9) have already been defined as missing values.
Run FREQUENCIES in SPSS to get a frequency distribution for the variable P3_POLINT1. There are only four categories for this variable so we don’t need to recode it. What does the frequency distribution tell you about the level of political interest in the U.S. and what are the implications for national political campaigns?
Now we want to compare men and women in terms of their political interest so we can look at gender differences. Run CROSSTABS in SPSS to produce a crosstabulation of the two variables – D5_SEX and P3_POLINT1. Think carefully about which variable is your independent variable and which your dependent variable is. Put the independent variable in the column and the dependent variable in the row of your table. Tell SPSS to compute the appropriate percents, Chi Square, and an appropriate measure of association.
Write a paragraph describing the relationship between the respondent’s sex and political interest. Were males more or less likely than females to be interested in politics? How big was the gender difference for political interest? Use the percents, Chi Square, and the measure of association to help you describe this relationship.
Part V – Gender Differences in Voting
Now we’re going to consider voting. Keep in mind that we’re only looking at respondents’ reports of whether they voted and whether they voted for a particular candidate. There is lots of evidence that indicates that people over report whether they voted and voting for the winning candidate. Voting is clearly the socially desirable response and social desirability is a powerful influence on how people answer survey questions.
The GSS asks respondents who they voted for in the 2008 (Obama vs. McCain) and the 2012 (Obama vs. Romney) presidential elections. These variables are named P5_PRES08 and P6_PRES12. They also asked respondents whether they voted in these elections and the variables are named P7_VOTE08 and P8_VOTE12. Run FREQUENCIES in SPSS to get the frequency distributions. A good source of information for the actual percent of people who voted in these elections can be found on the United States Elections Project's website. Compare the percent who said they voted in the GSS with the actual voter turnout. The Roper Center for Public Opinion Research has the percent of votes cast for Obama in 2008 and 2012 on their website. Compare the actual percent vote for Obama with the percent who said they voted for Obama in the GSS. Write a paragraph describing your findings and what might account for these differences.
Now we want to compare men and women in terms of voting so we can look at gender differences. Run CROSSTABS in SPSS to produce four crosstabulations of sex with each of these four variables. Think carefully about which variable is your independent variable and which your dependent variable is. Put the independent variable in the column and the dependent variable in the row of your table. Tell SPSS to compute the appropriate percents, Chi Square, and an appropriate measure of association.
Write a paragraph describing the relationship between the respondent’s sex and voting. Were males more or less likely than females to vote? Were males more or less likely to vote for the Democratic candidate for president? How big were the gender differences for voting? Use the percents, Chi Square, and the measure of association to help you describe this relationship.[4]
Part VI -- Conclusions
Write a paragraph summarizing what you learned about gender differences in political attitudes and behavior. What are the implications of these findings for national political elections?
[1] Variable names are in all capitals.
[2] Values are in parentheses.
[3] Missing values indicate answers that do not provide valid information.
[4] The Gallup Poll has tracked the gender gap in presidential voting from 1952 through 2012. A good review of their findings can be found on the Gallup Poll's website..
