Week 11 Sociology in Action Workshop: One Store, Two Pay Ratios, and the Everyday Script

Part 1 — The Big Picture

This week you learned that sex is the body and gender is what a society expects, that people learn gender from six agents and keep doing it in everyday interaction, and that the Bureau of Labor Statistics found women's median weekly earnings were 83% of men's for full-time wage and salary workers in 2024. That 83% is a raw ratio of medians across all full-time jobs, not a comparison of the same job. In this workshop you read a small, made-up store's pay records, compute its raw ratio and the ratio inside each job, and see for yourself how the two can differ. Then you run the store's pattern through the three perspectives, observe doing gender in one setting from your own week, and ask a chatbot the same questions so you can catch where it goes wrong.

Time budget: Plan for about 90 minutes.

Part 2 — The Task

Guiding question: In one store's pay records, how far apart are the raw ratio and the same-job ratios, what can that difference show and not show, and how is gender done in one setting from your own week?

Workshop data: an illustrative grocery store's weekly pay records and your own doing-gender observation

Source: An illustrative dataset constructed for this workshop, not from a real store: a hypothetical list of 12 full-time workers with each one's job, recorded gender, and usual weekly pay, plus one observation you make in your own week.

• Rows: 12 workers, labelled Worker 1 to Worker 12, one per row of the scaffold's first table
• Store columns: worker number; job (cashier, stocker, or department lead); recorded gender (woman or man); usual weekly pay in dollars
• Observation rows: 4 rows you fill in from one setting in your own week

Part 3 — Materials & Procedure

Tools and materials

• Free public data tables (Census Bureau, Bureau of Labor Statistics, Pew Research Center, World Bank, Our World in Data, General Social Survey) plus a spreadsheet (Google Sheets or any free spreadsheet)
• A document or notebook for your written answers

Ways of working

• apply-a-perspective-to-a-case
• read-and-interpret-social-data
• structured-observation-and-reflection

Procedure

1. Open a blank sheet. In row 1 type the headers Worker, Job, Gender, and Weekly pay in columns A, B, C, and D. In rows 2 to 13 copy the twelve rows of the first table in Part 4. Tool: Free public data tables (Census Bureau, Bureau of Labor Statistics, Pew Research Center, World Bank, Our World in Data, General Social Survey) plus a spreadsheet (Google Sheets or any free spreadsheet). Check: Rows 2 to 13 hold Workers 1 to 12, and six rows are women and six are men.
2. Sort the sheet by Gender. In F2 type the median of the six women's weekly pay, using =MEDIAN( with the six women's pay cells, and in F3 do the same for the six men. Copy both results into the second table in Part 4. Tool: Free public data tables (Census Bureau, Bureau of Labor Statistics, Pew Research Center, World Bank, Our World in Data, General Social Survey) plus a spreadsheet (Google Sheets or any free spreadsheet). Check: Women's median sits well below men's median.
3. In F4 divide women's median by men's median and multiply by 100, for example =F2/F3*100, to get the store's raw earnings ratio, and round it to one decimal. In F5 subtract that ratio from 100 to get the gap. Record both. Tool: Free public data tables (Census Bureau, Bureau of Labor Statistics, Pew Research Center, World Bank, Our World in Data, General Social Survey) plus a spreadsheet (Google Sheets or any free spreadsheet). Check: The raw ratio is well under 100, and the gap is written beside it.
4. Sort by Job. For each job, find the women's median and the men's median inside that job, divide the first by the second, and multiply by 100 to get the same-job ratio. Record each in the third table in Part 4, and count how many of the six women and six men hold each job. Tool: Free public data tables (Census Bureau, Bureau of Labor Statistics, Pew Research Center, World Bank, Our World in Data, General Social Survey) plus a spreadsheet (Google Sheets or any free spreadsheet). Check: Each same-job ratio sits near 100, while most women hold one job and most men another.
5. Pick one setting from your own week where people of different genders interact, such as a team practice, a shift at work, a class discussion, a family meal, or an online game. Spend about 15 minutes noticing it, then fill in the observation frame in Part 4: what was done, the concept it shows, and why it matters. Describe actions, never name anyone, and never judge a person's sex or gender identity from how they look. Check: Every row of the observation frame names an action you saw, not a guess about a person.
6. Answer the analysis questions in Part 5, then do the AI-critique step in Part 6, or the equivalent route printed there, and write the 3–5 sentence report. Check: Every answer points to a value in your tables, a row of your observation, or a definition from this week, and your report quotes at least two errors with corrections.

Fallback route

When to use it: Use this route if no spreadsheet is available.

Work the same steps by hand or with a calculator. For each group, line up the weekly pay from lowest to highest and find the middle; with an even count, add the two middle values and divide by 2. Divide women's median by men's median and multiply by 100, subtract the ratio from 100, and repeat the ratio inside each job. Write every step in your document so it can be checked, complete every scaffold table, answer every analysis question, do the critique step, and submit the same items for equal credit.

This route earns the same credit as the primary route.

Part 4 — The Scaffold

These are the workshop's illustrative pay records; copy them into your sheet so every result comes from your own formulas.

Student scaffold table 1

Worker	Job	Recorded gender	Usual weekly pay (dollars)	Your note on this worker
Worker 1	Cashier	Woman	680
Worker 2	Cashier	Woman	700
Worker 3	Cashier	Woman	720
Worker 4	Cashier	Woman	740
Worker 5	Cashier	Man	700
Worker 6	Stocker	Woman	820
Worker 7	Stocker	Man	800
Worker 8	Stocker	Man	840
Worker 9	Department lead	Woman	1150
Worker 10	Department lead	Man	1100
Worker 11	Department lead	Man	1150
Worker 12	Department lead	Man	1200

Record the store-wide medians, the raw ratio, and the gap here so your reading rests on numbers you produced yourself.

Student scaffold table 2

Quantity	Your value
Women's median weekly pay (dollars)
Men's median weekly pay (dollars)
Raw earnings ratio (%)
Gap below 100

Compare inside each job here, so you can see how much of the store-wide gap comes from who holds which job.

Student scaffold table 3

Job	Women in this job	Men in this job	Women's median in this job (dollars)	Men's median in this job (dollars)	Same-job ratio (%)
Cashier
Stocker
Department lead

Use this observation frame to move from what you saw, to the concept it shows, to why it matters.

Student scaffold table 4

What I observed	Which concept it shows	So what
One action that followed a gender expectation
How someone else responded to it
One moment when someone broke the script, and the reaction
One way the setting's rules or structure shaped what people did

Part 5 — Analysis Questions

1. Report women's median weekly pay, men's median weekly pay, the store's raw earnings ratio, the gap below 100, and the same-job ratio for each of the three jobs, showing the formula or the arithmetic behind each.
2. Read the store's raw ratio four ways: what is measured, over whom, what it shows and does not, and whether it is a correlation, a cause, or neither. Then explain in two sentences why the raw ratio and the same-job ratios differ so much, and what that difference cannot tell you.
3. Run the store's pattern, women concentrated in the lower-paid job, through structural functionalism, conflict theory joined by feminist theory, and symbolic interactionism, one or two sentences each, naming each one's level of analysis. Then name two of the week's five explanations of the gender pay gap that could account for the job mix, state each at full strength, and declare no winner.
4. From your observation frame, describe one moment of doing gender and the response it drew, and one way the setting's structure shaped what people did. Which concept does each show, and at what level of analysis does each work?
5. Name two limits, such as that the store is illustrative and has only 12 workers, that a median from one, three, or four people is fragile, that weekly pay leaves out hours and experience, or that one 15-minute observation is a single setting, and say how each limit affects what you can conclude.
6. Choose one and answer it in 3–4 sentences: (a) a friend says the store's raw ratio proves the manager pays women less for the same work; what would you tell them, and what evidence would change your answer? (b) think of a job or role you know that is held mostly by one gender; without naming anyone, what might explain the pattern, and at what level does that explanation work?

Part 6 — AI-Critique Moment

Choose one equal-credit critique route. Route A: ask an approved AI tool to critique your completed work, then check its response against your own evidence. Route B is the no-AI equivalent printed below.

Approved tools: Claude, Gemini, ChatGPT, Grok, Microsoft Copilot.

Prompt to paste:

I've pasted my completed workshop tables above. An illustrative grocery store has 12 full-time workers. For each worker the store lists the job, the recorded gender, and the usual weekly pay in dollars: Worker 1, Cashier, Woman, 680; Worker 2, Cashier, Woman, 700; Worker 3, Cashier, Woman, 720; Worker 4, Cashier, Woman, 740; Worker 5, Cashier, Man, 700; Worker 6, Stocker, Woman, 820; Worker 7, Stocker, Man, 800; Worker 8, Stocker, Man, 840; Worker 9, Department lead, Woman, 1150; Worker 10, Department lead, Man, 1100; Worker 11, Department lead, Man, 1150; Worker 12, Department lead, Man, 1200. Please do five things. First, find women's median weekly pay, men's median weekly pay, the store's raw earnings ratio, and the ratio inside each job. Second, tell me who wrote "Doing Gender" and in what year, and which perspective reads traditional gender roles as complementary roles. Third, tell me whether this table proves that the store discriminates against women or proves that the gap comes from choices. Fourth, explain why women at a store like this prefer cashier jobs. Fifth, use the national figure that women earn 83% of what men earn to tell me how much less Worker 2 is paid than she should be.

Test the response for these likely failures:

• Chatbots often add an outside figure with no source, such as a confident national gap for women and men in the same job, or a named study that supposedly settled why the gap exists.
• Chatbots often credit doing gender to Goffman or Mead, give it the wrong year, or credit the reading of gender roles as complementary to conflict theory.
• Chatbots often explain why women prefer cashier work from a stereotype about what women like or are good at, with no source.
• Chatbots often say the table proves discrimination, or proves that the gap is all choices, because women are concentrated in the lower-paid job.
• Chatbots often apply the national 83% or the store's raw ratio to Worker 2 and announce that she is underpaid by a set amount.

In 3–5 sentences, say what the chatbot got right, quote at least two sentences it got wrong, and correct each one with evidence from your tables or this week's definitions.

Equivalent route (no AI required)

No AI account is required for this workshop. This route assesses the same objectives, Objective 6 (analyze race and ethnicity and sex, gender, and sexuality as socially constructed categories — prejudice, discrimination, and institutional racism; gender socialization and 'doing gender'; the earnings gap and its competing explanations — reasoning from documented evidence in the source's own categories rather than from anecdote or stereotype) and Objective 1 (apply the sociological imagination — connecting personal troubles to public issues — and the three major theoretical perspectives (structural functionalism, conflict theory, symbolic interactionism) to interpret a social phenomenon, naming the level of analysis each works at and placing the discipline's founders with the ideas and works they are known for), takes comparable effort of about the same 90 minutes, uses the same rubric, and earns the same credit. Instead of the chatbot, critique this flawed analysis, printed here in full: "The store's raw ratio proves that the manager discriminates against women. A national study shows that women earn 82 cents for the same job. Goffman wrote Doing Gender in 1959, and conflict theory says gender roles are complementary. Women prefer cashier work because they are better with customers. So Worker 2 is paid about 17 percent less than she should be, because the national ratio is 83%." Mark every error you can find, quote at least two, and correct each one in 3–5 sentences with evidence from your tables or this week's definitions. Submit the marked-up analysis and your correction in place of the chatbot report and share link.

Part 7 — What to Submit

• All four completed scaffold tables, including your observation frame
• Written answers to all six analysis questions
• The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Sociology in Action Workshop report on an illustrative store's pay records and one doing-gender observation: four completed tables (the pay records with your notes, the store-wide medians and raw ratio, the same-job comparison, and your observation frame), written answers to six analysis questions, and a critique of a chatbot's answers to the same questions, or, on the equivalent route, a marked-up correction of the printed flawed analysis. Submit in any accessible file type or as a link; a recorded response may be submitted as audio or video with a transcript, or as text. Choose how you show it: written answers, a recorded explanation with a transcript, or a labelled diagram of the two kinds of ratio and your observation with short notes; every form is graded by the same scoring criteria.

Rubric

The rubric below shows how each submitted part is evaluated; bands are full, partial, or none.

Workshop evaluation criteria

Criterion	Full	Partial	None
Computing the medians, ratios, and gap	Both store-wide medians, the raw ratio, the gap below 100, and all three same-job ratios are computed from the workshop's figures with the formulas or arithmetic shown, and each ratio is labelled raw or same-job.	Most values are computed, but one median or ratio is missing or wrong, a step is not shown, or the ratios are not labelled.	No values are reported, or the values are invented rather than computed.
Reading the ratios: raw, same-job, and what neither shows	The answer reads the raw ratio four ways, calls the link between gender and job an association rather than a cause, explains why the raw and same-job ratios differ, and says the comparison cannot show why women and men hold different jobs.	The answer reads the ratio but either treats it as a same-job comparison, treats the pattern as a cause, or leaves out what the difference cannot show.	No answer is given, or the raw ratio is read as proof of one explanation.
Three perspectives and the doing-gender observation	The pattern is run through all three perspectives with each level named, two explanations of the gap are stated fairly without a verdict, and the observation names a real moment of doing gender and a structural influence, describing actions rather than any person.	One perspective or level is missing, one explanation is stated unfairly, or the observation names actions without tying them to a concept.	No perspective analysis or observation is given, or the observation judges people rather than describing actions.
Critique and correction	The chatbot critique report or the marked-up flawed analysis quotes at least two errors and corrects each with evidence from the tables or this week's definitions; both routes earn this band equally.	The chatbot critique report or the marked-up flawed analysis names an error but corrects it without evidence, or corrects only one; both routes earn this band equally.	No chatbot critique report or marked-up flawed analysis is submitted, or the output is pasted without any check; both routes are scored the same way.
Limits and reflection	Two real limits are named with their effect on the conclusion, and the chosen reflection option is answered with a reason.	One limit is named, or a limit is named without its effect, or the reflection gives no reason.	No limit or reflection is given.

Quality Gate

• Every median, ratio, and gap in your tables comes from your own formulas or your own hand calculation from the workshop's figures, never from memory or a chatbot.
• Every ratio is labelled as a raw ratio or a same-job ratio.
• Your reading calls the link between gender and job in the table an association, not a cause.
• Your answers never apply the national 83% or the store's raw ratio to one worker.
• Your perspective answer states each account at full strength and declares no winner.
• Your observation describes actions in a setting, names no one, and never judges anyone's sex or gender identity from appearance.
• No statistic, study, or source is invented anywhere in the submission.
• The critique quotes the chatbot or the flawed analysis and corrects at least two errors with evidence.