| Course | PS 323 Psychology of Gender |
|---|---|
| Unit | Unit 5 |
| Paper type | Gender and work paper |
| Length | About 1,030 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | BS in Psychology |
| Updated | October 2026 |
Free sample paper for PS 323 Unit 5
Eighty-Three Cents and What It Does Not Adjust For: A Gender and Work Paper Reporting the Pay Gap With Its Population and Year, the Adjusted Analyses and Each Explanation Attributed to Its Source
Student Name
Psychology, Herzing University
PS 323: Psychology of Gender
Instructor Name
August 4, 2026
Eighty-Three Cents and What It Does Not Adjust For: A Gender and Work Paper Reporting the Pay Gap With Its Population and Year, the Adjusted Analyses and Each Explanation Attributed to Its Source
Which Figure to Lead With
Sources report the gender pay gap with different numbers because they measure different things. This paper leads with the most widely cited official figure and then explains what it does and does not adjust for. In its report on women's earnings in 2024, the U.S. Bureau of Labor Statistics (BLS, 2025) found that women who worked full time in wage and salary jobs had median usual weekly earnings equal to 83 percent of the median for men in the same category. In 1979, the first year with comparable data, the figure was 62 percent. The population is full-time wage and salary workers in the United States; the measure is median weekly earnings; the year is 2024. The Bureau notes that the comparison does not control for factors such as job skills, responsibilities, experience or specialization, so it describes a difference in earnings, not its causes.
Why Sources Report Different Numbers
Readers often meet several pay-gap figures in the same week and conclude that someone is wrong. Usually each figure measures something different. Weekly earnings for full-time workers, the Bureau's measure, compare people who all work at least thirty-five hours a week, but among full-time workers men tend to work somewhat longer weekly hours than women, which widens a weekly comparison relative to an hourly one. Annual earnings figures, used in other federal reports, include differences in weeks worked across the year. Hourly wage figures, used in much academic research, remove differences in hours altogether. Medians and means also differ, because high earners pull means upward, and the gap is larger at the top of the distribution. Some figures include part-time workers and some exclude them. None of these choices is wrong; each answers a different question. A careful paper names the measure, the population and the year for every figure it reports, and it does not combine figures from different measures into a single trend. When sources disagree, the first step is to check whether they are measuring the same thing, which they often are not.
What Adjusted Analyses Show
Economists have asked how much of the raw gap remains once measurable differences between men and women workers are taken into account. Blau and Kahn (2017) used the Panel Study of Income Dynamics, a long-running national survey of U.S. households, to study the gap from 1980 to 2010. They found that the gap declined considerably over the period. By 2010, conventional human capital variables, such as education and years of experience, taken together explained little of the remaining gap, while differences in occupation and industry remained important. A portion of the gap remained unexplained after all measured factors were included. The authors also found that the gap had narrowed much more slowly at the top of the wage distribution than in the middle or bottom.
Two points follow. An adjusted gap is not the true gap, because some of the adjusted factors, such as occupation, may themselves reflect gendered constraints or choices. And an unexplained gap is not a measure of discrimination, because it may include factors the survey did not measure. Blau and Kahn treat it as consistent with discrimination as one contributor, alongside other explanations.
Explanations, Each Attributed
Occupation, industry and hours
Blau and Kahn (2017) identify occupational and industry differences as the most important measured factor by 2010. Goldin (2014) argued that a large part of the remaining gap, especially among highly educated workers, arises because many jobs pay disproportionately more for long, inflexible hours, and women more often take positions or reduce hours in ways that trade pay for flexibility. On her account, the gap would shrink if jobs paid more proportionately for hours worked.
Career interruptions and parenthood
Blau and Kahn (2017) note that women's workforce interruptions and shorter hours remain significant in high-skilled occupations. Correll et al. (2007) tested one mechanism directly. In a laboratory experiment, participants evaluated fictitious job applicants whose resumes were identical except for signals of parenthood. Mothers were rated as less competent and committed and were offered lower recommended starting salaries than equally qualified women without children, while fathers were not penalized and were sometimes favored. In a companion audit study, employers called back childless women more often than mothers with matched applications. The design isolates parental status as the only difference between applications, which is what allows the authors to attribute the difference to it.
Discrimination
Blau and Kahn (2017) conclude that experimental evidence strongly suggests discrimination cannot be ruled out as a contributor. The Correll et al. audit study is one example of such evidence, specific to mothers. The paper does not estimate how much of the overall gap discrimination accounts for, because the sources reviewed do not provide a single figure.
Do I Have to Conclude What Causes the Pattern?
No single cause is settled by this evidence, and the assignment does not require one. What the evidence supports is a set of contributing factors, each with its own support: occupational and industry differences, the structure of pay for long hours, career interruptions and parenthood, and some discrimination. Their relative weight differs across the wage distribution and has changed over time. A paper that reports this honestly is stronger than one that settles on a single explanation the sources do not. It also leaves room for the reader to see which explanations are best supported, rather than having one chosen for them.
Data This Paper Does Not Use
Company pay data from a writer's employer would be both confidential and unrepresentative of the labor market, and it would not show causes either. The figures here come from a national statistical agency and a nationally representative survey, which allow statements about the U.S. workforce as a whole and about change over time. Neither source can describe a particular workplace, and neither should be used to judge whether any individual is paid fairly; that question requires information about the specific job, the person's work and the employer's pay practices.
References
Blau, F. D., & Kahn, L. M. (2017). The gender wage gap: Extent, trends, and explanations. Journal of Economic Literature, 55(3), 789-865. https://doi.org/10.1257/jel.20160995
Correll, S. J., Benard, S., & Paik, I. (2007). Getting a job: Is there a motherhood penalty? American Journal of Sociology, 112(5), 1297-1339. https://doi.org/10.1086/511799
Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 104(4), 1091-1119. https://doi.org/10.1257/aer.104.4.1091
U.S. Bureau of Labor Statistics. (2025). Highlights of women's earnings in 2024 (BLS Reports). https://www.bls.gov/opub/reports/womens-earnings/2024/home.htm
Reading the PS 323 Unit 5 instructions
The fifth PS 323 unit asks students to write about gender and work with careful use of figures. Expect to report each figure with the population it describes and the year it was collected, explain what any analysis of a gap adjusted for and what it could not, and attribute every proposed explanation to its source. When sources report different numbers, lead with an official figure and explain how others differ in measure or population. The paper does not have to reach a conclusion about cause; reporting what the evidence supports is enough. Pay data from your own employer are confidential and unrepresentative, so national sources are the right basis. A short section reconciling figures from different sources is often welcome.
How the PS 323 Unit 5 example is put together
Opening with the Bureau's 2024 figure, the sample states its population, measure and year and what the Bureau says it does not control for. A section explains why weekly, hourly and annual figures and medians and means differ. Blau and Kahn's analysis of 1980 to 2010 is reported with what adjusted and unexplained gaps can and cannot mean. Explanations follow under attributed headings: occupation, industry and hours with Goldin; career interruptions and parenthood with Correll and colleagues' experiment and audit study; and discrimination. A section explains why no single cause is chosen, and the close explains which data the paper avoids. Each figure is followed immediately by its population, measure and year.
Reading the PS 323 Unit 5 rubric
Herzing's rubric for the gender and work paper usually allots points to accurately reported figures, attention to what analyses adjust for, attributed explanations, careful handling of causation and clear writing. Figures earn credit when population, measure and year accompany each. Adjustment scores when the writer explains what an adjusted or unexplained gap can show. Attribution is often heavily weighted, rewarding papers in which every explanation names its source. Causation earns points when the writer avoids settling a single cause the evidence does not support. Clarity is credited when competing figures are reconciled rather than left to confuse. Explaining why different sources report different figures is usually credited as careful reading.
PS 323 Unit 5 help: mistakes that cost points
Gender and work papers lose points when they report a pay gap figure without its year, population or measure. Another frequent weakness is mixing weekly, hourly and annual figures as if they were the same. Students often treat an unexplained gap as a direct measure of discrimination, or treat an adjusted gap as proof there is no problem. Some assert a single cause. Others use employer pay data, which is confidential and tells nothing about causes. Leaving out how the gap differs across the wage distribution is a quieter omission worth avoiding. Comparing a figure from one year with a figure from another as if they were simultaneous also misleads. Explanations should each carry a source; an unattributed explanation reads as opinion.
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PS 323 Unit 5 questions, answered
Which figure should I lead with when sources report different numbers?
Lead with the one your readings supply, then show the others and explain why they differ. Differences usually come from the population sampled, the year, and whether hours, occupation or experience were controlled for. A paper that reports three versions and accounts for the spread demonstrates more than one that picks the largest number and cites it confidently.
Do I have to reach a conclusion about what causes the pattern?
Usually not, and claiming one is riskier than declining. Most sections ask you to report the candidate explanations, say what evidence supports each, and state what remains unexplained. That is a conclusion, just a properly bounded one. If your instructions do require a position, hold it to what your cited studies support and mark the parts still contested.
Can I use pay data from the company I work for?
No, and this one matters. Salary bands, headcount by grade, promotion lists and performance ratings are your employer's confidential records, often covered by an agreement you signed, and a graded paper is read outside every control around them. Published labor statistics and peer-reviewed studies give you numbers you can cite, date and defend, which internal data never would.
Where can I find a free PS 323 Unit 5 sample paper?
The whole PS 323 Unit 5 gender and work paper is free above, with the official figure, the adjusted analyses, attributed explanations and margin notes. Focusing on hiring or promotion? Pass along your instructions and a paper on that question comes back at no cost.
Which figure should a PS 323 Unit 5 paper lead with?
An official figure stated with its measure, population and year. The sample leads with the Bureau of Labor Statistics weekly earnings ratio for 2024 and then explains how other figures differ.