| Course | PS 323 Psychology of Gender |
|---|---|
| Unit | Unit 7 |
| Paper type | Intersectionality analysis |
| Length | About 990 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 7
Ninety-Two Percent That Hides Seventy-Two: An Intersectionality Analysis of 2024 Weekly Earnings Holding Gender and Race Together Through Every Comparison
Student Name
Psychology, Herzing University
PS 323: Psychology of Gender
Instructor Name
August 18, 2026
Ninety-Two Percent That Hides Seventy-Two: An Intersectionality Analysis of 2024 Weekly Earnings Holding Gender and Race Together Through Every Comparison
The Framework and Its Origin
Intersectionality is a named framework with an origin. The legal scholar Kimberlé Crenshaw introduced the term in 1989 to describe how antidiscrimination law, by treating race and sex as separate categories, failed Black women whose experiences of discrimination could not be captured by either category alone, and she developed it further in a 1991 article on violence against women of color (Crenshaw, 1991). Her point was not simply that people belong to several groups. It was that the combination produces experiences, and patterns in data, that an analysis of one category at a time cannot see.
In psychology, Cole (2009) argued that using the framework in research means asking three questions of any analysis: who is included within a category, what role inequality plays, and where there are similarities across groups that a single-axis view would miss. This paper applies those questions to one set of data, holding gender and race together in every comparison rather than naming them once and then analyzing one at a time.
The Data
The data come from the Bureau of Labor Statistics report on women's earnings in 2024 (U.S. Bureau of Labor Statistics [BLS], 2025). The measure is median usual weekly earnings for people employed full time on wages or salaries in the United States during 2024. The report gives figures for women and men within four groups defined by race and Hispanic ethnicity.
| Group | Women's median weekly earnings | Men's median weekly earnings | Women's earnings as a percent of men's in the same group |
|---|---|---|---|
| All workers | $1,043 | $1,261 | 83% |
| White | $1,061 | $1,288 | 82% |
| Black | $922 | $1,002 | 92% |
| Asian | $1,365 | $1,726 | 79% |
| Hispanic | $832 | $963 | 86% |
What a Single-Axis Reading Shows
A reading that looks only at gender, within each racial group, produces the right-hand column. On that column, Black women appear to fare best, earning 92 percent of Black men's median, and Asian women worst, at 79 percent. A reading that looks only at race would compare the groups' totals and note that Asian workers earned the most and Hispanic workers the least. Each reading is accurate as far as it goes.
What Holding Both Axes Together Shows
Cole's first question, who is included within a category, changes the picture. The 92 percent figure for Black women is a comparison with Black men, whose median of $1,002 is well below that of White men. Compared with White men, the largest group of men in the data, Black women's median of $922 is about 72 percent, and Hispanic women's median of $832 is about 65 percent. These comparisons are calculated from the report's medians. The small gender ratio among Black workers does not mean Black women are close to parity; it reflects the fact that Black men's earnings are also low. The single-axis reading made Black women look advantaged, while the intersectional reading shows them earning well below the men with the highest median in this comparison.
The Asian figures show the reverse pattern. Asian women had the highest median of any group of women, above White men's median, yet the largest gap relative to men in their own group, because Asian men's median was the highest of all.
Cole's second question, what role inequality plays, points to what these figures cannot show. Medians by group describe earnings; they do not identify the causes of differences, which include differences in occupation, region, education, age and discrimination, in varying combinations. The intersectional reading reveals where the gaps are; explaining them requires further analysis.
Cole's third question, where there are similarities, also applies. In every group, women's median earnings were below men's. That shared pattern is real, and an intersectional analysis does not deny it; it shows that its size and meaning differ across groups.
Why This Matters Beyond Earnings
The earnings data make the framework's logic easy to see because the numbers are public and precise, but the same logic applies to most findings in the psychology of gender. A study reporting an average difference between women and men may be describing mostly White, middle-class participants, so its conclusion about women may not hold for women in other groups. Cole (2009) made this point about psychological research in general: the category women, as sampled in many studies, includes some women far more than others. Holding a second axis in view prompts a reader to ask who was in the sample before accepting a conclusion about a whole category. It also changes what counts as an explanation. A gap that is smaller in one group may not mean that group has less inequality; as the earnings data show, it may mean that both women and men in that group face disadvantages that a gender-only comparison hides.
Writing About Groups One Is Not Part Of
The framework does not require that a writer belong to the groups analyzed, but it does require care: describing groups through the data and the research rather than through assumptions, using the categories the sources use, and avoiding claims about experience that the data cannot support. Earnings medians describe economic outcomes; they do not describe how anyone feels about their work or their identity.
When Studies of the Specific Combination Are Missing
This analysis uses official data that cross gender with four racial and ethnic groups. Many questions in psychology lack studies of the specific combinations a writer is interested in. When that happens, the honest course is to say so, report what is known about each component and avoid inferring the experience of a combined group by adding the two separately, which is exactly the error the framework was introduced to correct.
Limits
The categories in the data are broad. Asian and Hispanic, for example, include groups with very different earnings, and the report's figures cannot show those differences. Medians describe the middle of each group, not its spread. And the data concern full-time wage and salary workers only, leaving out part-time and self-employed workers, whose patterns may differ. A fuller intersectional analysis would also add further axes, such as age or disability, where data allow.
References
Cole, E. R. (2009). Intersectionality and research in psychology. American Psychologist, 64(3), 170-180. https://doi.org/10.1037/a0014564
Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241-1299. https://doi.org/10.2307/1229039
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
The Herzing PS 323 Unit 7 instructions
The seventh PS 323 unit asks students to apply intersectionality as a framework. Expect to credit the term to the legal scholarship that introduced it, then hold two or more axes together through every claim rather than naming them in an opening paragraph and analyzing one at a time. Two axes are usually enough for a paper of this length. When studies of the specific combination you are interested in do not exist, say so and avoid inferring the combined experience by adding each axis separately. Writing about groups you are not part of is acceptable when the analysis relies on data and research rather than assumptions about experience.
How the PS 323 Unit 7 example is put together
The framework's origin in Crenshaw's work is set out first, followed by Cole's three questions for psychological research. The data are introduced with their source, measure, population and year, in a table that crosses gender with four racial and ethnic groups. A section shows what single-axis readings conclude. The core section then applies Cole's questions in turn, calculating comparisons with White men, explaining the Black and Asian patterns, and noting both what the data cannot explain and the shared pattern across groups. Sections on why the framework matters beyond earnings, writing about other groups, missing studies and limits close the paper. Every comparison in the paper names a group defined by both gender and race.
Where the points sit in the PS 323 Unit 7 rubric
Herzing's rubric for the intersectionality analysis usually weighs accurate attribution of the framework, two or more axes held together throughout, data reported with source and population, use of a structured approach such as Cole's questions and recognition of limits. Attribution earns credit when the legal origin is named. Holding axes together is often the decisive criterion, rewarding papers in which every claim concerns a group defined by both. Data earn points when sourced precisely. A structured approach is credited when it organizes the analysis rather than decorating it. Limits score when broad categories and missing groups are acknowledged. Calculated comparisons that reveal what a single-axis reading hides are frequently what earns the top band.
PS 323 Unit 7 help: mistakes that cost points
Intersectionality papers lose points when they define the term in an introduction and then analyze gender and race separately. Another common weakness is listing identities without showing how their combination changes a finding. Students often infer a combined group's experience by adding two single-axis results, which is the error the framework was introduced to correct. Some omit the framework's origin. Others treat broad categories as uniform. Making claims about how people feel, when the data describe outcomes, is a further overreach. Adding a calculated comparison with a reference group is a simple way to show what the framework reveals. Presenting the framework as a list of identities, rather than as a method for reading data, misses its point. Forgetting to report the data's source and year is a basic omission markers notice.
Get a PS 323 Unit 7 example written to your instructions
Post us the Unit 7 instructions with your PS 323 rubric and the axes or population the assignment specifies. We write a custom example that credits the framework, declares its axes early, carries the combination through every claim and reports where the literature runs thin. First custom sample free, back in 24 to 48 hours.
More PS 323 papers and psychology samples
- PS 323 Unit 1: Concepts and terminology paper
- PS 323 Unit 2: Theories of gender development
- PS 323 Unit 3: Cognitive and ability differences paper
- PS 323 Unit 4: Socialization paper
- PS 323 Unit 5: Gender and work paper
- PS 323 Unit 6: Gender and health paper
- PS 323 Unit 8: Applied or policy paper
- PS 101 Unit 7: Psychological disorder overview
- PS 105 Unit 7: Adulthood and aging paper
- PS 130 Unit 7: Ethics and professional conduct paper
- PS 210 Unit 7: Adolescent development paper
PS 323 Unit 7 questions, answered
How many axes should the analysis hold?
Two carried properly beats four mentioned. The criterion rewards keeping the categories in contact, and each additional axis multiplies what you have to evidence, so most undergraduate papers do better with a tight pair. If your instructions name the categories, use those. Say in the opening which you selected and why the pairing has research behind it.
What if I cannot find studies on the specific combination?
Report that, because it is a finding in itself. Say which searches you ran, what the literature covers on each category separately, and where work on the combination is missing or small. A paper that documents a gap and stops there is stronger than one that quietly infers what the missing studies would have shown.
Should I write about a group I am not part of?
You can, and the requirement is the same either way: cite scholarship by and about the people you are writing on, and make claims only at the strength your sources support. What goes wrong is not the writer's own position but unsourced description of what an experience is like. Attribute, quote sparingly, and let the cited voices carry the characterization.
Where can I find a free PS 323 Unit 7 sample paper?
This page publishes the full PS 323 Unit 7 intersectionality analysis free, with the earnings table, the calculated comparisons, Cole's questions and margin notes. Holding different axes or a different outcome? Send the instructions and an analysis built that way is written for you free.
How many axes should a PS 323 Unit 7 analysis hold?
Two is usually enough to show what the framework adds. The sample holds gender and race together in every comparison and notes that age or disability could be added where data allow.