Week 7 — Sociology-in-Action Workshop · "Income Is Not Wealth"

Course: Introduction to Sociology (SOC 1) · Silver Oak University (fictional sample) · Prof. Adeyemi
Objective: Objective 5 — read real income/wealth/poverty data and distinguish income (a flow) from wealth (a stock) · SLO B (reason from evidence) & SLO A (apply theory)
Worth 50 points · Sociology Workshops group = 15% of the grade · Workshop 7
Mode this week: data interpretation (other weeks alternate with observation/reflection workshops). No special tools — just a browser and an approved chatbot.

This is the course's signature weekly component. Every instructional week has one Sociology Workshop. Some weeks you'll read real social data (a chart or table from the Census, Pew, BLS, the World Bank, or Our World in Data); other weeks you'll observe and reflect on your own social world. Either way you'll end by catching an AI's mistakes. All external resources are links — nothing to buy or download.

Part 1 — The Big Picture

This week you met the single most important distinction in the study of inequality: income vs. wealth. Income is a flow — the money a household receives over a period (wages, salary, benefits), like water from a faucet. Wealth (net worth) is a stock — everything a household owns minus what it owes (home equity, savings, investments, minus debt), like the level of water already in the tub. Two households with the same income can have wildly different wealth. This workshop turns that distinction on real U.S. data from the Census Bureau — and shows you why even the official numbers measure the faucet, not the tub.

The guiding question: When the news reports a number about American inequality, is it telling you about income (a flow) or wealth (a stock) — and what does that number actually show, and not show?

Part 2 — The Data (identified, linked, and pre-stated — verified live)

We're reading two official figures from the U.S. Census Bureau, both for calendar year 2023 (the reports were published September 10, 2024). Open the pages yourself and find these numbers — that habit is the whole point.

Figure A — Median household income.
- Indicator: real median household income, United States.
- Figure (verified on the Census page): $80,610 in 2023 (the Census notes this was a 4.0% increase from $77,540 in 2022).
- Source (links only): U.S. Census Bureau, Income in the United States: 2023 (Report P60-282).
🔗 https://www.census.gov/library/publications/2024/demo/p60-282.html

Figure B — The official poverty rate.
- Indicator: the official U.S. poverty rate (share of people below the official poverty threshold).
- Figure (verified on the Census page): 11.1% in 2023 — about 36.8 million people. (The same page also reports the Supplemental Poverty Measure (SPM) at 12.9% — notice there is more than one poverty measure.)
- Source (links only): U.S. Census Bureau, Poverty in the United States: 2023 (Report P60-283).
🔗 https://www.census.gov/library/publications/2024/demo/p60-283.html

A wealth note (and a verification rule): these Census figures are about income (and an income-based poverty line). They do not measure wealth. Wealth is far more concentrated than income, and it's tracked by a different source — the Federal Reserve's Distributional Financial Accounts (🔗 https://www.federalreserve.gov/releases/z1/dataviz/dfa/distribute/chart/). If you want to talk about a wealth share (e.g., "the top 1% own X%"), you must read it off the Fed's own page first. This workshop does not assert any specific wealth figure — that's exactly the discipline you're practicing: read the number at its source before you use it.

Part 3 — Read-the-Data Scaffold (fill this in)

Work the scaffold for Figure A (median household income, $80,610, 2023) — and answer the wealth question at the end. This is the what-is-measured → over-what → what-it-shows-and-not → correlation-or-causation move.

Part 4 — Analysis Questions

Answer in a sentence or two each:
1. In your own words, what is the difference between income and wealth? Use the faucet-vs-tub image, and explain why wealth is typically more unequally distributed than income.
2. The official poverty rate (Figure B) was 11.1% in 2023. What does this rate measure, and name one thing it does not capture (think: wealth? within-group differences? the causes of poverty? the fact that the SPM gives a different number?).
3. A friend says, "Median household income went up in 2023, so everyone is better off." Using what a median is, explain why that conclusion doesn't follow.
4. Pick one of the two big accounts of stratification from this week — the Davis-Moore (functionalist) thesis or the conflict view — and explain in two sentences how it would interpret a large income (or wealth) gap. (Remember: the data describe the gap; the perspectives interpret it.)

Part 5 — AI-Critique Moment (required — this is the BYOAI step)

Now bring in your approved chatbot (Gemini, Claude, or ChatGPT) and be the sociologist who checks its work.

1. Ask it: "What was U.S. median household income in 2023, what was the official poverty rate, and what share of U.S. wealth does the top 1% hold? Does this prove the U.S. is or isn't a meritocracy?"
2. Check everything it says against the sources and this week's ideas:
   - Did it blur income and wealth? Watch for it quoting a wealth share and a median income as if they were the same kind of number, or labeling one as the other. (Chatbots do this constantly — it's the week's signature error.)
   - Did it invent or misdate a statistic? Verify the median income ($80,610) and the poverty rate (11.1%) on the Census pages, and verify any wealth share on the Federal Reserve page. If you can't find a number at the source — or it's tagged to the wrong year — treat it as fabricated or misdated, and say so.
   - Did it slide from a number to a verdict? A descriptive statistic does not by itself "prove" the system is fair or unfair, and a one-year change does not prove a cause. Catch any leap from data to causal/moral conclusion.
3. Write 3–4 sentences reporting what the AI got right and at least one thing you had to correct, verify, or flag — an income/wealth mix-up, an unverifiable or misdated figure, or a jump from a number to a "this proves meritocracy is real/fake" verdict. (If it happened to get everything right, say how you verified each claim at the source — that's the skill.)

The habit all term: the tool drafts, you judge — and you verify every number at its source. A chatbot will confidently confuse income with wealth or invent an exact percentage — catching it is the point.

Part 6 — What to Submit

Submit a single document (or text entry) with: your completed Part 3 scaffold, your Part 4 answers, and your Part 5 AI-critique paragraph. Note the source and year for any figure you reference. Due Sunday, Oct 18, 11:59 p.m. (50 points).

Instructor answer key & model responses — REMOVE BEFORE PUBLISHING TO STUDENTS

All figures below were verified live at the source on the build date (2026-06-29). Median household income $80,610 (2023): U.S. Census Bureau, Income in the United States: 2023 (Report P60-282), seen in the report "Highlights." Official poverty rate 11.1% (2023), ~36.8 million people; SPM 12.9% (2023): U.S. Census Bureau, Poverty in the United States: 2023 (Report P60-283), seen in the report "Highlights." No wealth figure is asserted in this workshop; students must read any wealth share off the Federal Reserve's page.

Model worked scaffold (Figure A — median household income $80,610, 2023):
- What is measured? The annual money income of the median (middle) U.S. household — half of households earn more, half less. It's a measure of income (a flow), and a median (not an average, so it isn't pulled up by the very rich). It is not wealth.
- Over what population and period? All U.S. households, calendar year 2023, from the Current Population Survey (CPS ASEC).
- What it shows / does NOT show: it pins the middle of the income distribution. It does not show wealth, does not reveal the spread (how far apart the top and bottom are), does not show who is in the middle, and does not explain why incomes differ across groups.
- Correlation or causation? The ~4% rise from 2022 to 2023 is a descriptive change. By itself it does not tell us the cause (the labor market, policy, inflation adjustment, and measurement all move at once). A statistic describes; it rarely isolates a cause alone.
- Income vs. wealth check: two households at $80,610 could differ enormously in wealth — one might own a paid-off home and investments (high net worth), the other rent and carry debt (low or negative net worth). Same flow, different stock.

Expected answers:
- Q1: income = money received per period (a flow, the faucet); wealth = assets minus debts (a stock, the tub level). Wealth is more unequal because it accumulates and compounds across generations (inheritance, home equity, investment growth) while income is earned fresh each year. (Full credit does not require a specific wealth statistic — only the correct concept and, if a number is used, a source.)
- Q2: the official poverty rate measures the percentage of people whose household money income is below the official threshold (an income-based, near-absolute line). It does not capture wealth, within-group differences, the causes of poverty, or the fact that the SPM (12.9%) counts things the official measure leaves out — there's more than one poverty number.
- Q3: a median is the middle value; it can rise while the bottom stagnates or the top pulls away. "Everyone is better off" doesn't follow from a single midpoint — the median hides the distribution.
- Q4: Davis-Moore (functionalist): the gap reflects unequal rewards motivating scarce, trained talent into more important roles. Conflict: the gap reflects power and the reproduction of advantage — who could access the training/credentials, and who sets the pay rules. Full credit names the perspective and keeps "describe vs. interpret" straight.
- Part 5 (AI-critique): full credit for a specific catch — most commonly the AI blurring income and wealth (e.g., reporting a wealth share as if it were income, or treating median income as a wealth figure), inventing or misdating a statistic (unverifiable at the Census/Fed), or jumping from a number to a "this proves meritocracy is/ isn't real" verdict. Full credit also if the student verified each figure at the source (Census for income/poverty, Federal Reserve for wealth) and reported how.

Grading rubric — 50 points

Quality gate (self-checked): the two published figures asserted in this workshop — median household income $80,610 (2023) and the official poverty rate 11.1% (2023) (with SPM 12.9% and ~36.8M people in poverty) — were verified live at the U.S. Census Bureau (Reports P60-282 and P60-283) on the build date; source and year are stated for each. No wealth figure is asserted — the workshop deliberately reframes the wealth point around the skill (read it at the Federal Reserve source) rather than stating an unverified number, per the discipline's load-bearing rule. The income-vs-wealth distinction (flow vs. stock), the meaning of a median, and the absolute/relative poverty framing are all accurate. The AI-critique explicitly targets the income/wealth confusion, fabricated/misdated statistics, and the number-to-verdict (correlation-as-causation / data-as-moral-conclusion) slip — the discipline's load-bearing AI risks. No correlation is presented as causation: the ~4% income rise and any poverty-rate change are explicitly framed as descriptive, not causal.