Call For Proposals

Standard Survey Variables

Below is a summary of the standard variables provided to all contributors to CivicPulse omnibus surveys. These variables consist of five categories:
(1) survey metadata, (2) demographics for policymaker positions only, (3) demographics for all positions, (4) constituent demographics, and (5) survey weights. 

Survey Metadata Variables 

StartDate 

The time and date when the survey was started. 

EndDate 

The time and date when the survey was completed. For respondents that did not complete the survey, this variable records the time of their last activity on the survey. 

 

Finished 

1 = Respondent completed the survey 

0 = Respondent did not complete the survey 

Gov_type 

A variable indicating the government position of the respondent. Its values are: “county,” “municipality,” and “township.” 

State 

A variable indicating which state the respondent resides in. 

 

Demographics for Policymaker Positions Only 

Ideo_5 

In general, do you think of yourself as: 

  • Very conservative 

  • Somewhat conservative 

  • Moderate, middle of the road 

  • Somewhat liberal 

  • Very liberal 

  • Not sure 
     

Party 

Generally speaking, do you usually think of yourself as a … 

  • Democrat 

  • Republican 

  • Independent 

  • Other party (please specify): ___ 
     

Party_Indep  

Do you think of yourself as closer to the Democratic Party or the Republican Party? 

  • Democratic Party 

  • Republican Party 

  • Neither 

 

Demographics for All Positions 

Sex¹

What is your sex? 

  • Male 

  • Female 
     

Age 

In what year were you born? 

    (1910 or earlier, 1911-1915, … , 2006 or later) 

Education 

What is the last grade of school you completed? 

  • Less than high school 

  • High school graduate 

  • Technical/trade school 

  • Some college 

  • College graduate 

  • Some graduate school 

  • Graduate degree 

 

White_nonhispanic 

Respondents are asked their race and ethnicity using questions taken from the US Census (see below). To maintain respondent confidentiality, the original answers to these questions are not provided. Instead, we construct ‘White_nonhispanic’ which takes on a ‘1’ if they indicate being non-Hispanic and White, and ‘0’ if they identify as Hispanic or non-white.  

 

Ethnicity 

Are you of Hispanic, Latino, or Spanish origin? 

  • No, not of Hispanic, Latino, or Spanish origin 

  • Yes, Mexican, Mexican Am., Chicano 

  • Yes, Puerto Rican 

  • Yes, Cuban 

  • Yes, another Hispanic, Latino, or Spanish origin 
     

Race 

Which of the following best describes your race/ethnicity? Please check all that apply:
 

  • White 

  • Black/African American 

  • Asian/Asian American (includes East Asian, South Asian, Southeast Asian, and Pacific Islander) 

  • Native American 

  • Other (please specify):___ 

Constituent Demographics 

To provide additional information about the constituents which respondents represent, we match respondents’ geographic locations to the U.S. Census (97% match rate).  Using this method, we provide three variables about respondents’ constituents: the proportion of the population that is college-educated (College_prop), the proportion living in an urban area (Urban_prop), and the population size (Population). To ensure confidentiality of the respondent, each variable is binned: College_prop and Urban_prop are binned into terciles. 
 

College_prop 

The proportion of 25-years-or-older residents in the given geographic unit who have completed a 4-year, post-secondary degree. This data was taken from 2015 American Community Survey.  

Urban_prop 

The proportion of residents in the given geographic unit who reside in an urban area. This data is taken from the 2010 Census. 

Population 

The total number of residents living in the given geographic unit. This data is taken from the 2015 American Community Survey. 

Survey Weights 

Unlike with surveys of the U.S. mass public—which rely on Census demographic data about the aggregate U.S. population to generate weights—we do not have demographic data about the aggregate population of elected local government officials (with the exception of gender, which we can code based on first names). However, we can mitigate some of the possible survey sample bias by reweighting based on the demographics of constituent areas. To this end, we employ a conventional post-stratification raking procedure using the Census variables listed in the previous section. We follow the methodology outlined in DeBell and Krosnick (2009) for the American National Election Study (ANES).

¹ We use a first-name matching to historical Census data to determine respondent sex.  Respondents who cannot be matched with at least 95% confidence are given this question.

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