Lecture: Intersections: Gender, Class, Language, Religion, and Multiracial Identity
Lecture script · about 15–20 minutes spoken · Week 14
Opening
Picture two siblings at a kitchen table, filling in the same school form. They have the same mother and the same father. The older one checks two race boxes. The younger one checks one. Neither of them is wrong. The form counts what each person reports about themselves. In this lecture I want you to ask a harder question: what does a form, or a law, see and miss when it reads one category at a time?
You've built every tool you need for this. In Week 2, you met race, ethnicity, nationality, and a word I asked you to keep in your pocket: intersectionality. In Week 7, you worked the lending table and read a woman's line about the bank. In Week 10, you met Section 4(e) of the Voting Rights Act of 1965 and the federal term Hispanic or Latino. And last week, in Week 13, you traced the federal categories from 1977 to 2024. This week we read the places where those lines cross.
Here's the plan. We'll put intersectionality to work on more categories than race and sex. Then we'll read a 1967 Supreme Court case about marriage, and a census option that lets you check more than one race. Then we'll name colorism, read rules about language and religion, revisit the lending table, and finish with one family's story. One word on names before we start. Multiracial is the Census Bureau's word for people who report more than one race. People who do so name themselves in many ways, and this course follows the words people choose.
1. Intersectionality, put to work
Think about a break room at work. A new rule goes up on the wall, and it says the same thing to everyone. But a rule that reads people one category at a time can still land hardest on the people where two categories meet.
The law has its own version of that problem. The Civil Rights Act of 1964 outlawed discrimination based on race, color, religion, sex, or national origin in employment and in places of public accommodation. Count that list with me: race, color, religion, sex, national origin. That's 5 separate categories, each named on its own.
In 1989, a legal scholar named Crenshaw wrote an article called "Demarginalizing the Intersection of Race and Sex." Crenshaw argued that antidiscrimination law that looks at race alone or at sex alone fails people, such as Black women, whose experience is shaped by both at once. That's intersectionality: the idea that overlapping categories, such as race and sex, produce experiences that neither category alone describes. It is not the adding together of identities. And notice the timing. Crenshaw wrote 25 years after the 1964 law, and the point was that a law reading its 5 categories one at a time can miss a person standing where two of them meet.
This week you widen the lens. Gender is the social roles, expectations, and identities a society attaches to being a woman, a man, or another identity. Class is a person's or family's position in the economy, shaped by work, income, property, and wealth. Gender, class, language, religion, and citizenship all overlap with race and ethnicity. Here's the test to carry all week. Ask what a one-category check would see. Then ask what it would miss.
Pause and try this. A friend says, "A person with three identities has three separate problems, so add them up." What would intersectionality say back?
Hold the word "add" in your mind for a second.
Here's the answer. Intersectionality says the overlap makes its own experience, so you can't find it by adding up one category at a time. The question isn't how many categories a person has, but what each one-category check would miss.
2. Loving v. Virginia and every couple across a racial line
Think about a wedding you've been to. Two families sit on two sides of the room, and they may differ in religion, language, home town, or race. For much of the country's history, in many states, one of those differences could stop the wedding by law.
That changed in 1967. Loving v. Virginia is the 1967 Supreme Court decision that unanimously struck down laws prohibiting interracial marriage. Listen to what the Court struck down: the laws themselves. It didn't carve out one pair of groups. So the ruling reaches every couple whose marriage crosses a racial line.
Let's put it on the timeline. Brown v. Board of Education, in 1954, held that "Separate educational facilities are inherently unequal." Loving v. Virginia came in 1967, 13 years after Brown. The Civil Rights Act came in 1964, so Loving came 3 years after that. In other words, laws against marriage across racial lines outlasted both.
Now connect it to this week's question. A marriage law that reads race is also a law about family. Families formed across racial lines are one place where a child may grow up naming more than one heritage. Keep that thought, because it leads straight into the census form.
Pause and try this. A classmate says Loving v. Virginia was only about Black and white couples. What's the fix?
Think about what, exactly, the Court struck down.
Here's the answer. The Court struck down the laws prohibiting interracial marriage, not one pairing within them. So the ruling reaches every couple whose marriage crosses a racial line.
3. One or more races, and what a count can tell you
Go back to those two siblings. Before 2000, a federal form would have asked each of them to pick one race. The older sibling's two-box answer had nowhere to go.
Here's what changed. One or more races is the option in the 1997 federal standards that lets a respondent select more than one race on a federal form, used from the 2000 census on. That's 3 years after the standards, and 33 years after Loving v. Virginia. Multiracial is the Census Bureau's word for people who report more than one race. And self-identification is the rule that a census or survey records the categories a person chooses for themselves. That's why both siblings can be counted as they report.
Now the counts, and I'll give each one its year and its source. The Census Bureau's count of Multiracial people, in millions, went from 9 in 2010 to 33.8 in 2020. That's 24.8 more, in millions, over 10 years. It sounds like a huge jump. But the Bureau expects the change was largely due to improvements in the questions' design, data processing, and coding. A count is a fact about people and about the form at the same time, and when the form changes, the count can change even if the people don't.
The same form shows a second meeting point. The Census Bureau counted Hispanic or Latino people, in millions, at 62.1 in 2020, which is 18.7 percent of the population. They may be of any race. In 2020 the form asked about Hispanic or Latino origin in one question and about race in another. So each of those people also answered the race question. On that form, an ethnicity category and the race categories meet in one person's answers.
Pause and try this. Someone reads the jump from 9 to 33.8, in millions, as proof that the multiracial population grew that much in 10 years. What's missing from that reading?
Think about what else changed between those two censuses.
Here's the answer. The question changed. The Census Bureau expects the change was largely due to better question design, processing, and coding, so the rise isn't population growth alone.
4. Colorism: a line drawn inside one group
Think about a family photo album. An aunt remembers a relative being praised, or teased, for being lighter or darker than a cousin. Nobody in that story belongs to a different group, yet skin tone was still being used to rank people.
That has a name. Colorism is unequal treatment based on skin tone, including within a single racial or ethnic group, which makes it different from racism between groups.
Let me give you two hiring stories to sort. In the first, a manager turns away every applicant from one racial group, whatever their skin tone. The line runs between groups. That's discrimination between groups. In the second, a manager hires applicants from the manager's own group but favors the lighter-skinned ones among them. The line runs inside one group, by skin tone. That's colorism. Now here's the catch. A check that asks only whether the second manager hired people of that group would find nothing wrong. Only a check that also asks about skin tone finds the pattern.
So colorism is one more overlap: race and skin tone are related, but not the same.
Pause and try this. A club admits members of every group but puts only lighter-skinned members of one group in its photos. Is that colorism, or discrimination between groups?
Ask yourself where the line is drawn.
Here's the answer. It's colorism. The club draws its line inside one group, by skin tone, while it admits members of every group.
5. Language and religion: rules that touch several lenses
Picture a warehouse that posts a rule: no languages other than English on break. The rule names no race, no ethnicity, and no country. So let's read it the way this course reads every rule. What it says: workers may speak only English, even on their own time. Who made it: the employer. Whom it affects: workers whose first or home language isn't English. And language often runs with ethnicity and national origin, and sometimes with citizenship too. What it leaves out: it doesn't name the groups it lands on. The Civil Rights Act of 1964 lists national origin, but it doesn't list language by name. That's one reason a language rule has to be read through more than one category at once.
The law has met that overlap before. Linguistic rights are protections for people's use of their own languages in public life, such as voting, schooling, and work. You met one in Week 10. Section 4(e) of the Voting Rights Act of 1965 protected citizens educated in American-flag schools taught in a language other than English from English-literacy requirements. There, language and citizenship met in one voter.
Religion needs the same care, and this course treats it descriptively, never as a verdict on anyone's belief. One ethnic group can hold many faiths. Last week you heard that Arab American communities are Christian, Muslim, Jewish, and of other faiths. And one faith gathers people of many ethnic groups. So you can't read a person's religion off their ethnicity, or their ethnicity off their religion.
Here's one more case, a borderline one from Week 2 that we discuss and never key: a workplace dress code that bans a hairstyle common in one group. Read it through this week's lens, and a new question appears. A hairstyle rule may land on people where a racial group and a gender meet, which a check for race alone or for sex alone could miss. Anzaldúa's 1987 book, Borderlands/La Frontera: The New Mestiza, is a primary work of Chicana writing about identity formed at the borders of nations, languages, cultures, and genders.
Pause and try this. The break-room rule names only language. Name two other categories it can touch at the same time.
Go back to whom the rule affects.
Here's the answer. Ethnicity and national origin, and sometimes citizenship. Language often runs with all three, so the rule lands on the people where they meet.
6. Class and place in the lending table
Think about two families with the same jobs and the same savings. One lives on a street the lender's map rates highly, the other across a highway on a street it rates poorly. Their records match, but their addresses don't.
Week 7 named that rule. Redlining is refusing loans or other credit to people because of the neighborhood they live in, whatever their own creditworthiness. In the 1930s, the Home Owners' Loan Corporation drew maps that graded city neighborhoods A through D by the racial, ethnic, and economic characteristics of residents. Hear that phrase again with this week's ears. Race, ethnicity, and class were bundled together into one rating for a place.
Let's rework the course's lending table, which is an illustrative model, not any real city. In A-rated neighborhoods, 180 of 200 applications were approved. Divide 180 by 200 and multiply by 100, and you get 90 percent. In D-rated neighborhoods, 20 of 200 were approved, which is 10 percent. The gap is 90 minus 10, or 80 percentage points. We say percentage points because it's a difference between two percentages. And per neighborhood, A-rated ones got 18 approved loans each, against 2 in D-rated ones, a ratio of 9 to 1.
One limitation, said plainly. The table is a model of how a rating rule produces unequal outcomes. It isn't a measure of any group's income or wealth, and this course gives no such figure. What it shows is the mechanism: when a rating bundles race and class into an address, a check for either one alone misses how the rule works.
Pause and try this. Someone says this gap is about money alone, so it has nothing to do with race. Using the maps' own wording, what's the fix?
Recall what the maps graded neighborhoods by.
Here's the answer. The maps graded neighborhoods by the racial, ethnic, and economic characteristics of residents together. So race and class were bundled into one rating, and the gap is an overlap, not class alone.
7. E2, read through several lenses
Think of a story your family tells about a move: who went first, who followed, and what it cost.
The course archive is an illustrative collection; its excerpts are written for this course, not real people's words. E2 is a woman whose family moved north in the Great Migration in the 1940s, interviewed in the 1990s. She says the family left in 1943. Her father went first, to work in a shipyard, and sent for them that spring. On the train they sat in the car set aside for Black passengers until they were out of the South. In the new city nobody told them where to sit, but there were neighborhoods where the bank would not lend to them. And her mother said it was different, not finished.
You read E2 in Week 7 for the bank. Let's walk it again in the field's order. What it says, you've heard. Who made it: it's a first-person account recorded decades later. Whom it affected: the narrator, her mother, her father, and the rest of the family. Several lenses meet in them. Race shows in the train car and the bank's map. Gender shows in who went first. Class and place show in where the family could borrow and buy.
What it leaves out matters too. It doesn't say what work the mother or the narrator did, or where the narrator went to school, or whether being women shaped their chances. An intersectional reading asks those questions. It doesn't invent answers. On the timeline, the move came in 1943, and the Fair Housing Act came in 1968, 25 years later. And here's a comparison. Section 4(e) answered a rule where language and citizenship met; E2 shows a rule about race and place. In both, a one-category reading misses the people at the overlap.
So here's the reading in one plain sentence. E2 is an illustrative account of the Great Migration in which race, gender, class, and place shaped one family at once, so an intersectional reading sees the bank's map and the train car together.
Pause and try this. A summary of E2 says the mother must have worked as a cook. What's wrong with that?
Think about what the excerpt says, and what it doesn't.
Here's the answer. E2 never says what work the mother did. An intersectional reading names that silence and turns it into a question; it never invents a detail for an excerpt.
Closing
Let me pull it together. Intersectionality is overlap, not addition, and the 1964 law's 5 categories, read one at a time, can miss a person where two meet. Loving v. Virginia, in 1967, struck down laws prohibiting interracial marriage, for every couple across a racial line. Since the 2000 census, you can report one or more races, and the jump in the Multiracial count is mostly better measurement. Colorism draws its line inside one group. A language rule or a dress code can touch several categories at once, and religion is read descriptively. The lending rating bundled race and class into place. And E2 shows race, gender, class, and place in one family, with its silences turned into questions.
Next in this module come the slide deck, the Readings & Resources page, the lecture tutorial, the practice set, and the quiz. Next week, in Movements, Solidarity, and the Course Synthesis, you'll see how groups worked together across the very lines we read here.
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