Week 14 — Sociology-in-Action Workshop · "Read the Labor Data"
Course: Introduction to Sociology (SOC 1) · Silver Oak University (fictional sample) · Prof. Adeyemi
Objective: Objective 7 — the economy & work; reading a labor statistic · SLO B (read & evaluate social data; correlation vs. causation) & SLO A (apply a perspective)
Worth 50 points · Sociology Workshops group = 15% of the grade · Workshop 14
Mode this week: data interpretation (other weeks alternate with observation/reflection workshops). No special tools — just a browser and an approved chatbot. All sources are links — nothing to buy or download.
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. This week is data mode — and labor data is a place where a real number gets twisted into an unsupported causal story, so we go slow and careful.
Part 1 — The Big Picture
This week you studied the economy and work — the sectors, capitalism vs. socialism, and the changing nature of work from the factory to the gig economy. One of the clearest long-run changes in American work is the decline of labor unions. Unions are organizations through which workers bargain collectively over pay and conditions; their rise and fall is woven into the story of industrial and post-industrial work. This workshop reads the official union-membership data from the Bureau of Labor Statistics — and practices the skill that protects you from headlines: reading a labor statistic for exactly what it shows, and refusing to read into it a cause it can't establish.
Three habits we'll drill:
- Read the denominator — the "union membership rate" is a percent of wage and salary workers, not of the whole population. Misread the denominator and you misread the number.
- A trend is not a cause — the rate fell over four decades. That's a real, sourced fact. It does not, by itself, tell us why it fell, and a co-trend with something else (like rising inequality) is not proof that one caused the other.
- Read the fine print — even the BLS flags a comparability caveat in the 2025 data. Data literacy means reading the footnotes, not just the headline number.
The guiding question: When you see a labor statistic like "the union membership rate is 10%," what exactly does it measure, what does it show over time — and what does it not show?
Part 2 — The Data (identified, linked, and pre-stated — verified live)
We'll work with the official U.S. union-membership figures. The numbers below were verified live at the source at build time; cite the source and year whenever you use one.
Source — U.S. Bureau of Labor Statistics: "Union Members — 2025" (news release).
🔗 https://www.bls.gov/news.release/union2.nr0.htm
- Indicator: the union membership rate — the percent of wage and salary workers who were members of unions — and the number of union members, from the Current Population Survey (CPS).
- What it shows (pre-stated, verified live): the union membership rate was 10.0% in 2025 (about 14.7 million wage and salary workers were union members). In 1983, the first year for which comparable data are available, the rate was 20.1% (17.7 million members). So the rate has roughly halved over about four decades — a long-run decline.
- Two more verified details (useful context): in 2025 the public-sector union membership rate (32.9%) was more than five times the private-sector rate (5.9%). And among full-time workers, union members had higher median weekly earnings than nonunion workers ($1,404 vs. $1,174) — but the BLS explicitly cautions this comparison "does not control for many factors" (occupation, industry, age, region), so it is not a clean estimate of a "union wage effect."
- The fine print (read it!): BLS notes that the 2025 estimates were produced using 11-month averages that exclude October (the October 2025 CPS was not collected due to a federal government shutdown), so 2025 annual estimates are "not strictly comparable" with other years. State this caveat if you use the 2025 number.
Historical context (optional) — BLS "Household data series: Union Membership Tables."
🔗 https://www.bls.gov/cps/cpslutabs.htm
- The BLS landing page for the long-run union-membership series — if you want to see the decline year by year behind the two endpoints (1983 → 2025). (BLS home: https://www.bls.gov/.)
You only need the main source for the scaffold below, but read the fine-print box on the release page first — it's part of the lesson.
Part 3 — Read-the-Data Scaffold (fill this in)
Work the scaffold for the BLS union-membership figure. This is the move every careful reader makes.
| Prompt | Your answer |
|---|---|
| The figure (state the number(s) + year, with the source) | ______ |
| What is measured? (a rate of WHOM? union members vs. workers represented?) | ______ |
| Over what population & period? (whose rate; which years; from what survey?) | ______ |
| What does it show? (state the trend in one plain sentence — up or down, by how much) | ______ |
| What does it NOT show? (what conclusion would be unsupported by this number alone — e.g., why it fell?) | ______ |
| Correlation or causation? (is any causal claim attached? is it warranted? what's the fine-print caveat?) | ______ |
Part 4 — The Correlation-vs-Causation Drill (required)
Labor data is where a real trend gets turned into a false cause. Work both:
Drill 1 — the co-trend trap. Over roughly the same decades that the union membership rate fell (20.1% in 1983 → 10.0% in 2025), income inequality rose. A headline concludes: "The decline of unions caused inequality to rise."
- In 2–3 sentences, explain why this is not established by the two trends alone. Use the words correlation vs. causation and third variable / other changes: what else changed over those decades (think about the sector shift to services, globalization, automation, law and policy) that could affect both? What would you need to establish a cause (recall Week 2)?
Drill 2 — the denominator trap. Someone reads "the union membership rate is 10.0%" and says: "So only 10% of Americans have jobs with a union."
- In 1–2 sentences, explain what's misread here: whom is the 10.0% a percentage of, and why "10% of Americans" is the wrong denominator. (Bonus: how does "membership" differ from being "represented by" a union?)
Part 5 — Analysis Questions
Answer in a sentence or two each:
1. In your own words, what does the union membership rate measure, and why does it matter that it's a percent of wage and salary workers rather than of everyone?
2. The 2025 figure comes with a BLS comparability caveat (11-month average, missing October). Why does a careful reader care about a footnote like that when comparing 2025 to earlier years?
3. Apply one perspective to the union decline: e.g., what would a conflict theorist note about workers' bargaining power, or what would a structural-functionalist note about how the economy coordinates labor as it shifts from factories to services? (One short paragraph — and keep it evenhanded.)
4. Pick the single figure you used and finish this sentence carefully: "This number shows , but it does NOT show ."
Part 6 — 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.
- Ask it: "What is the current U.S. union membership rate, how has it changed since the 1980s, and did the decline of unions cause rising inequality?"
- Check everything it says against the BLS source above and the week's ideas:
- Did it invent or misdate a statistic? Labor numbers are a favorite hallucination for chatbots. Verify any figure it gives at the source (the BLS "Union Members" release). If you can't find it there, treat it as fabricated — and say so. (For reference, the verified figures here are: union membership rate 10.0% in 2025 vs. 20.1% in 1983, per BLS, "Union Members — 2025," released Feb 18, 2026.)
- Did it slide from correlation to causation — assert that the decline of unions caused rising inequality from the co-trend alone? Catch it and name the missing pieces (other changes; no controlled comparison).
- Did it take a political side — present the union question (or capitalism vs. socialism) as if one answer were obviously right — instead of laying out the competing arguments fairly?
- Did it misread the denominator ("10% of Americans") or overgeneralize ("all gig workers are exploited," "unions always raise everyone's wages")? Flag it; the data describe rates and trends, not group character or proven effects. - Write 3–4 sentences reporting what the AI got right and at least one thing you had to correct, verify, or flag — a fabricated/misdated number, a correlation-as-causation leap, a denominator misread, a one-sided take, or an overgeneralization. (If it happened to get everything right, say how you verified each claim against the BLS source — that's the skill.)
The habit all term: the tool drafts, you judge. With labor data especially, a chatbot will confidently invent a number or turn a trend into a cause — catching it is the point.
Part 7 — What to Submit
Submit a single document (or text entry) with: your completed scaffold (Part 3), your two correlation-vs-causation drills (Part 4), your Part 5 answers, and your Part 6 AI-critique paragraph. Name the source + year for every figure you cite. Due Sunday, Dec 6, 11:59 p.m. (50 points).
Instructor answer key & model responses — REMOVE BEFORE PUBLISHING TO STUDENTS
Every figure below was verified live against the authoritative source at build time — U.S. Bureau of Labor Statistics, "Union Members — 2025," news release USDL-26-0229, released Feb 18, 2026 (Current Population Survey). The key grades the data-reading reasoning — not a single "right" sentence.
Verified figures (state the source + year):
- Union membership rate: 10.0% in 2025 (about 14.7 million members); 20.1% in 1983 (17.7 million members) — the first comparable year. The rate has roughly halved over the period (a long-run decline). (BLS, "Union Members — 2025.")
- Public vs. private (2025): public-sector rate 32.9%, more than five times the private-sector rate 5.9%.
- Earnings (2025, full-time): union members' median weekly earnings $1,404 vs. nonunion $1,174 — but BLS cautions this does not control for occupation, industry, age, or region, so it is not a clean "union effect."
- Comparability caveat: 2025 estimates use 11-month averages excluding October (October 2025 CPS not collected due to the federal government shutdown); BLS states 2025 is "not strictly comparable" with other years.
Model scaffold:
- The figure: union membership rate 10.0% (2025), down from 20.1% (1983) — BLS, "Union Members — 2025."
- What is measured: the percent of wage and salary workers who are union members (not the whole population; and "members" is narrower than workers "represented by" a union, who include some covered by a contract without being members).
- Population & period: U.S. wage and salary workers; annual figures, 1983 and 2025; from the Current Population Survey.
- What it shows: the union membership rate roughly halved over about four decades — a steep long-run decline.
- What it does NOT show: it does not tell us why the rate fell, does not establish that unions raise or lower anyone's wages, and (for 2025) is not strictly comparable to earlier years per the BLS caveat.
- Correlation or causation: the rate describes a trend; it proves no cause. A co-trend with rising inequality is a clue, not a verdict.
Drill 1 (model): The two trends moving together is a correlation, not causation. Over those decades many things changed at once — the shift from manufacturing to services, globalization, automation, and changes in labor law and policy — any of which could affect both unionization and inequality. To establish that the union decline caused rising inequality you'd need the kind of controlled comparison from Week 2 (holding other factors constant), not two trend lines side by side. So the headline overreaches.
Drill 2 (model): "10.0%" is a percent of wage and salary workers, not of all Americans (it excludes, e.g., the self-employed and people not working), so "only 10% of Americans have a union job" misreads the denominator. (Bonus: being represented by a union — covered by a contract — is a slightly larger group than union members, so the "represented" rate is a bit higher than the membership rate.)
Expected answers (Part 5):
- Q1: the rate is the share of wage and salary workers who are union members; the denominator matters because using "all Americans" (or all workers including the self-employed) would change the number and its meaning.
- Q2: the 2025 figure rests on an 11-month average missing October, so it isn't strictly comparable to full-year figures from other years — a careful reader notes the caveat before drawing a sharp year-to-year conclusion.
- Q3: any accurate, evenhanded application — e.g., conflict: fewer union members can mean less collective bargaining power for workers relative to employers; functionalist: as the economy shifts from heavily-unionized factories to services, labor is coordinated through different arrangements. Full credit for an accurate, fair application that doesn't decree a political verdict.
- Q4: any figure correctly bounded — e.g., "The 10.0% rate shows the share of wage and salary workers in unions in 2025, but it does not show why unionization fell, nor that unions cause any particular wage outcome, nor (strictly) a clean comparison to other years."
- Part 6 (AI-critique): full credit for a specific catch — most commonly a fabricated/misdated union number, a correlation-as-causation leap ("unions' decline caused inequality"), a denominator misread ("10% of Americans"), a one-sided political take, or an overgeneralization. Full credit also if the student verified each AI claim at the BLS source and reported how.
Grading rubric — 50 points
| Criterion | Full | Partial | None |
|---|---|---|---|
| Read-the-data scaffold (Part 3) — correctly identifies the figure as a rate of wage and salary workers and a decline, names population/period/source, and states what it does/doesn't show (14) | 14 | 7–11 | 0–5 |
| Correlation-vs-causation drills (Part 4) — names the co-trend/correlation-vs-causation error and the denominator misread; refuses the causal leap (14) | 14 | 7–11 | 0–5 |
| Analysis questions (Part 5) — accurate read of the rate and the comparability caveat; a correct, evenhanded perspective application; a well-bounded "shows/does-not-show" (12) | 12 | 6–10 | 0–4 |
| AI-critique (Part 6) — names a specific thing checked/corrected: a fabricated/misdated stat, a correlation-as-causation leap, a denominator misread, a one-sided take, or an overgeneralization, with verification at the BLS source (10) | 10 | 5–8 | 0–3 |
Quality gate (self-checked): the figures in this workshop were verified live at the authoritative source and are cited with source + year — U.S. Bureau of Labor Statistics, "Union Members — 2025" (USDL-26-0229, released Feb 18, 2026): union membership rate 10.0% in 2025 (14.7 million members) vs. 20.1% in 1983 (17.7 million); public-sector 32.9% vs. private-sector 5.9%; union vs. nonunion median weekly earnings $1,404 vs. $1,174 (BLS notes this is uncontrolled). The 2025 comparability caveat (11-month average excluding October due to the federal government shutdown) is stated explicitly. The entire workshop is built around keeping correlation ≠ causation front and center: Drill 1 defuses the "unions' decline caused inequality" co-trend leap, and the AI-critique step requires the student to verify any figure at the BLS source and to refuse a causal leap. No correlation is presented as causation; no figure is fabricated; the union/inequality debate and capitalism-vs-socialism are handled evenhandedly, with no group stereotyped.
~ Prof. Adeyemi's edition · Fall 2026 · built with thecoursemaker.com