5.4.1: Inequities in Employment During COVID-19
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- 63493
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)It has long been known that people of color have historically experienced discrimination in hiring and employment and that these same populations have different access to fair salaries, paid sick leave, and unemployment benefits (Yearby and Mohapatra 2020; Quillian et al. 2017; McMurtry et al. 2019; Tessler et al. 2020; Bleich et al. 2019; Findling et al. 2019). A recent study considered these inequalities in the context of the COVID-19 pandemic in the United States (Gemelas et al. 2022). Of particular interest was whether people of color experienced higher levels of employment loss in frontline and non-frontline occupations during the onset of the pandemic.
The data for the study was based on the Current Population Survey of the Bureau of Labor Statistics. This survey is based on a representative sample of 60,000 households in the United States. The data used for the study were based on two time points, January and June of 2020 (Gemelas et al. 2022). The observed variables included the occupation of the individual, their racial or ethnic identity, and whether the individual was employed or not. The occupation variable reflects the job position of the individual, grouped using broad categories such as Healthcare Practitioners and Support and Protective Service. The categories were then grouped as either being frontline; that is, an occupation that is considered critical and requires in person interaction, or non-frontline. This is a qualitative variable with a nominal measurement scale. The racial or ethnic identity used the categories Black or African American, Asian American, White, Hispanic or Latinx, and Non-Hispanic or Latinx. This is also a qualitative variable with a nominal measurement scale. Finally, the question as to whether someone was employed or not is also a qualitative variable on a nominal measurement scale.
The analysis of the data collected in this study is mostly based on calculations with the number of working employed in several employment sectors. The percentages of individuals unemployed within each race category and whether the occupation is considered frontline or non-frontline was computed. Table 5.5 is adapted from a small portion of Table 1 in the research article showing the first two frontline occupation categories (Gemelas et al. 2022). The calculations are typical of those contained in the original research article. The data in this table are based on counting the number of observations in each category of a nominal variable. This is a permissible calculation with this type of data because we only need to identify whether each observation of the nominal variable is in the category of interest. Once these counts are obtained then it is permissible to compute the difference between the counts and the corresponding change in percent. All the remaining calculations shown in this paper are based on percent changes in the number of workers within specified categories of race, year, and whether the job was a frontline job or not. All these types of calculations are permissible with these types of counts.
Table 5.5. The number of healthcare practitioners and protective service workers employed in the first two quarters of 2020, adapted from Table 1 (Gemelas et al. 2022).
|
Occupation |
First Quarter Employed |
Second Quarter Employed |
Change |
Percent Change |
|
Healthcare Practitioners |
23,258,585 |
21,754,243 |
-1,504,342 |
-6.47 |
|
Protective Service |
2,033,623 |
2,024,401 |
-9,222 |
-0.45 |