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Essay: Research suggests that more women volunteer than men

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  • Subject area(s): Sociology essays
  • Reading time: 3 minutes
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  • Published: 15 September 2019*
  • Last Modified: 22 July 2024
  • File format: Text
  • Words: 661 (approx)
  • Number of pages: 3 (approx)

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Research suggests that more women volunteer than men.  Some researchers have hypothesized that this is due to social roles and activities.

Wymer (2011) looked at it from a biological perspective, trying to understand preferences for various aspects of volunteering with the differences between the sexes. His research showed that females prefer to support organizations that help the needy or work with infants, young children, or teenagers. Women also prefer to volunteer for organizations where leadership is shared and their opinions matter. Wymer also found that males prefer volunteer roles that have some extent of risk of danger or where they can be in positions of authority.  

Methods

The data in this study is from the General Social Survey conducted in 2014. The General Social Survey is currently conducted by the National Opinion Research Center (NORC) every two years to gather data to monitor and explain trends in attitudes, behaviors, and characteristics about American society. The population of the GSS are people 18 and older living in households in the United States. The sample is selected through stratified random sampling, so that the results are mathematically accurate to represent the general population. The sample consisted of 2,538 people. The GSS uses a three wave, rotating panel design. Data is collected by conducting face to face survey interviews that take around 90 minutes.

Variables

I want to be able to explain why people volunteer. To do this, I will compare people who have volunteered and people who have not volunteered with respondents levels of general happiness. The variable I used to measure volunteering was volchrty. Respondents were asked, “During the past 12 months, how often have you done each of the following things E. Done volunteer work for a charity”. Responses were measured nominally from 0 to 9 accordingly; 0 = “IAP”, 1= “More than once a week”, 2= “Once a week”, 3= “Once a month”, 4= “At least 2 or 3 times in the past year”, 5= “Once in the past year”, 6= “Not at all in the past year”, 8= “DK”, 9= “NA”. I chose to recode the responses into a binary variable to separate those who have volunteered in the past 12 months and those who have not volunteered in the past 12 months. I labeled the new variable volchrtybin and re coded values 1 through 5 to the new value 1, 6 to the new value 0, and all other values as system missing. 1= has volunteered in the past 12 months, 0= has not volunteered in the past 12 months.

The independent variable I chose to use was happy. Respondents were asked, “Taken all together, how would you say things are these days– would you say that you are very happy, pretty happy, or not too happy?”. Responses were measured nominally in 6 categories from 0 to 9 accordingly; 0= “IAP”, 1= “Very happy”, 2= “Pretty happy”, 3= “Not too happy”, 8= “DK”, 9= “NA”. I chose to recode the responses into dummy variables to separate responses so that “Not too happy” would not be worth three times as much as “Very happy” to the computer. For the first dummy variable I labeled it hap1 and kept the value of 1 the same, but recoded values 2 through 3 to the 0, and all other values as system missing. The second dummy variable was labeled hap2 where values 1 and 3 were recoded to 0, 2 was recoded to 1, and all other values as system missing. The third dummy variable was hap3 where values 1 through 2 were recoded to 0, 3 was recoded to 1, and all other values system missing.

The control variables I used were sex and age. I recoded sex into a binary variable, sexbin, 1= females, 0= males. Age I had to recode into three dummy variables to separate age cohorts, and make sure variables are be normalized to use in univariate analysis. I recoded 18 through 29 as 1 30 through 89 as 0, and all other values as system missing for age1. Age2 was recoded as 30 through 49 as 1, 18 through 29 and 50 through 89 as 0, and all other values as system missing. Age3 was recoded as 50 through 69 as 1, 18 through 49 and 70 through 89 as 0, and all other values as system missing. Age4 was recoded as 18 through 69 as 0, and 70 through 89 as 1, and all other values as system missing.

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