Introduction

This study seeks to investigate gender differences in the US workforce. We aim to investigate whether there is a higher number of one gender to the other in the workforce. Research has depicted of the existing gender differences across different sectors of the workforce across the world. For instance, the construction industry is widely viewed as masculine while the hospitality industry is largely considered feminine. Over the years, however, researchers and scholars have depicted the increasingly bridging gender gap (Pleau, 2010; Powell, 2015).

A study by Feenstra (2019) depicted that in the year 2000, there existed a significant difference of about 30 % in the number of male and female construction workers in the US. This gap has, however, been decreasing over the years closing to about 12 % in 2013, but yet the difference was significant. In the hospitality industry, the number of female employees was about 17 % higher than the number of male employees. Progressively, the gap has narrowed down and stood at 6.2 % in 2014 (Evertsson, 2016). This has not been the case with the USA only but across many of the world countries. Another aspect of the US workforce which has depicted gender biasedness is salaries and remuneration. Research has depicted that across several industries, male employees are more likely to earn more than their female counterparts (Basu, 2013). The gaps have, however, been narrowing over the past decade.

The increasingly decreasing trends in the workforce gender gaps depict of the measures that have been taken by states and countries to ensure gender equality. For so long and across many countries, gender disparities have existed and there is now a need to have a more equal world (Frances, 2010). In this paper, the aim is to understand on whether or not the US workforce has complied with gender equality labor laws.

Sample

The study shall involve conducting a research on the gender differences in the US workforce. A sample to be included in the study shall involve the examination of the construction, hospitality, banking, education and health sectors of the workforce. Investigating whether or not there exists significant differences in the mean salaries of male and female employees in the sampled sectors shall help inform on whether the US workforce is balanced, gender-wise. The demographic variable that shall be used is the gender of employees across the different sampled sectors.

The study shall involve recruiting a sample size of 150 individuals, 30 from each of the five sectors (construction, hospitality, banking, education and health). The individuals shall be recruited on the basis of stratified random sampling.

Data collection

Data for this study will be collected from primary sources. A survey will be conducted asking the heads of recruitment of various sectors to provide a list of their employees across departments.

Analysis

The collected data shall be analyzed for difference in mean salaries for male and female employees across the different examined sectors.

The research question which the study seeks to answer is;

Is there a significant difference in the mean salaries of male and female employees in the US workforce?

Based on the research question the following hypothesis is formulated;

H₀: There is no significant difference in the mean salaries for male and female employees in the US workforce.

H₁: There exists a significant difference in the mean salaries for male and female employees in the US workforce.

In order to evaluate the study hypothesis, two samples t-test is carried out. The test statistic is calculated as follows;

The test statistic is evaluated at the 5% level of significance. A p-value less than 0.05 would imply the rejection of the null hypothesis while a p-value greater than 0.05 would imply failing to reject the null hypothesis that there exists no significant difference in mean salaries for male and female employees across the several sectors of the US workforce.

Conclusion

A rejection of the null hypothesis would imply the acceptance of the alternative hypothesis that there exists a significant difference in the mean salaries for male and female employees across the different sectors of employment in the US. This would mean that gender equality is not yet replicated in the workforce. A failure to reject the null hypothesis would, however, imply that there is no sufficient evidence to suggest that the workforce is gender-biased in terms of salaries and remuneration.

References

Basu, D. (2013). Dynamics of output and employment in the US economy. Cambridge Journal of Economics, 1077-1106.

Evertsson, M. (2016). Work interruptions and young womens career prospects in Germany, Sweden and the US. Work Employment & Society, 291-308.

Feenstra, R. (2019). US Exports and Employment. Journal of International Economics, 7-14.

Frances, T. (2010). Marking Difference and Negotiating Belonging: Refugee Women, Volunteering and Employment. Gender, Work & Organization, 277-281.

Pleau, R. (2010). Gender Differences in Postretirement Employment. Research on Aging, 267-303.

Powell, A. (2015). Gender differences in working at home and time use patterns: evidence from Australia. 571-589.

Survey

Please provide accurate responses to the below survey questions.

1. What is the name of your organization?
2. What is your gender?
3. Male   2. Female 3. Other
4. What is your age in years?
5. What is your role at the organization?
6. What is your education level?
7. Do you feel you are qualified for the present role?
8. Yes  2. No
9. For how long have you been working with the organization? (in years)
10. For how long have you been working at the current role? (in years)
11. I am satisfied with my present role
12. Strongly Agree 2. Agree 3. Neither Agree nor Disagree 4. Disagree 5. Strongly Disagree
13. My organization has as high number of female as male employees
14. Strongly Agree 2. Agree 3. Neither Agree nor Disagree 4. Disagree 5. Strongly Disagree
15. Are you treated fairly at the organization?
16. Yes 2. No
17. Are employees of either gender regarded equally at your organization?
18. What is your monthly salary?
19. Are you satisfied with your current salary?
20. Yes 2. No
21. Do you feel that colleagues of the other gender attract the same salary?
22. Yes 2. No
23. Have you ever experienced any workplace issue with the opposite gender?
24. Yes 2. No
25. What aspects do you think the management of your organization should improve in order to have a gender equal workplace?
26. What do you consider to be the most significant difference between male and female employees?
27. What is one thing you would like the opposite gender to know about your gender?
28. How likely would you recommend the organization to a friend?

Provide your answer on a scale of 1 to 10 with 1=Not at all likely and 10=Extremely likely.

Question #1 in the survey: “What is the name of your organization?”

Variable name: Qn1 

Variable description (label in spss): What is the name of your organization?

Variable values: none

Level of Measurement: Nominal  

Question #2 in the survey: “What is your gender?”

Variable name: Qn 2

Variable description (label in spss): What is the name of your organization?

Variable values: 1=Male, 2=Female

Level of Measurement: Nominal  

Question #3 in the survey: “What is your age in years?”

Variable name: Qn 3

Variable description (label in spss): What is your age in years?

Variable values: 1-100

Level of Measurement: Interval

Question #4 in the survey: “What is your role at the organization?”

Variable name: Qn 4

Variable description (label in spss): What is your role at the organization?

Variable values: none

Level of Measurement: Nominal  

Question #5 in the survey: “What is your education level?”

Variable name: Qn 5

Variable description (label in spss): What is your education level?

Variable values: none

Level of Measurement: Nominal  

Question #6 in the survey: “Do you feel you are qualified for the present role?

”

Variable name: Qn 6

Variable description (label in spss): Do you feel you are qualified for the present role?

Variable values: 1=Yes, 2=No

Level of Measurement: Nominal  

Question #7 in the survey: “For how long have you been working with the organization (in years)?”

Variable name: Qn 7

Variable description (label in spss): For how long have you been working with the organization?

Variable values: none

Level of Measurement: Interval

Question #8 in the survey: “For how long have you been working at the current role (in years)?”

Variable name: Qn 8

Variable description (label in spss): For how long have you been working with the organization?

Variable values: none

Level of Measurement: Interval

Question #9 in the survey: “I am satisfied with my present role”

Variable name: Qn 9

Variable description (label in spss): I am satisfied with my present role

Variable values: 1=Strongly Agree, 2=Agree, 3=Neither Agree nor Disagree, 4=Disagree 5=Strongly Disagree.

Level of Measurement: Ordinal

Question #10 in the survey: “My organization has as high number of female as male employees”

Variable name: Qn 10

Variable description (label in spss): My organization has as high number of female as male employees

Variable values: 1=Strongly Agree, 2=Agree, 3=Neither Agree nor Disagree, 4=Disagree 5=Strongly Disagree.

Level of Measurement: Ordinal

Question #11 in the survey: “Are you treated fairly at the organization?”

Variable name: Qn 11

Variable description (label in spss): Are you treated fairly at the organization?

Variable values: 1=Yes, 2=No

Level of Measurement: Nominal  

Question #12 in the survey: “Are employees of either gender regarded equally at your organization?”

Variable name: Qn 12

Variable description (label in spss): Are employees of either gender regarded equally at your organization?

Variable values: none

Level of Measurement: Nominal  

Question #13 in the survey: “What is your monthly salary?”

Variable name: Qn 13

Variable description (label in spss): What is your monthly salary?

Variable values: none

Level of Measurement: Scale

Question #14 in the survey: “Are you satisfied with your current salary?”

Variable name: Qn 14

Variable description (label in spss): Are you satisfied with your current salary?

Variable values: 1=Yes, 2=No

Level of Measurement: Nominal  

Question #15 in the survey: “Do you feel that colleagues of the other gender attract the same salary?”

Variable name: Qn 15

Variable description (label in spss): Do you feel that colleagues of the other gender attract the same salary?

Variable values: 1=Yes, 2=No

Level of Measurement: Nominal  

Question #16 in the survey: “Have you ever experienced any workplace issue with the opposite gender?”

Variable name: Qn 16

Variable description (label in spss): Have you ever experienced any workplace issue with the opposite gender?

Variable values: 1=Yes, 2=No

Level of Measurement: Nominal  

Question #17 in the survey: “What aspects do you think the management of your organization should improve in order to have a gender equal workplace?”

Variable name: Qn 17

Variable description (label in spss): What aspects do you think the management of your organization should improve in order to have a gender equal workplace?

Variable values: none

Level of Measurement: Nominal  

Question #18 in the survey: “What do you consider to be the most significant difference between male and female employees?”

Variable name: Qn 18

Variable description (label in spss): What do you consider to be the most significant difference between male and female employees?

Variable values: none

Level of Measurement: Nominal  

Question #19 in the survey: “What is one thing you would like the opposite gender to know about your gender?”

Variable name: Qn 19

Variable description (label in spss): What is one thing you would like the opposite gender to know about your gender?

Variable values: none

Level of Measurement: Nominal  

Question #20 in the survey: “How likely would you recommend the organization to a friend?”

Variable name: Qn 20

Variable description (label in spss): How likely would you recommend the organization to a friend?

Variable values: 1=Not at all likely, 10=extremely likely”.

Level of Measurement: Ordinal