Week 13 Community History Workshop: A Library Exhibit's Ten Family Papers

Part 1 — The Big Picture

A family's papers are a small record of how the law reached into everyday life. This week you traced who could become a citizen, from the naturalization law of 1790 and its 1870 extension to the Immigration and Nationality Act of 1952; read the Immigration Act of 1924, the 1965 law, and the Immigration Reform and Control Act of 1986; and followed the federal categories from 1977 to 1997 to 2024. In this workshop you code ten illustrative family papers from a library exhibit, linking each paper to the week's laws, then count, compare, and place the papers in time. You set the 1870 extension beside the 1952 law on the course's citizenship thread, which runs across five groups, catch a chatbot misstating a law or turning a federal box into biology, and reflect on what your own position lets you see.

Time budget: Plan for about 90 minutes.

Part 2 — The Task

Guiding question: Which of this week's laws show up in one library exhibit's ten family papers, how are they shared across the papers, and what can ten papers not tell you?

Workshop data: An illustrative library exhibit's ten family papers

Source: Ten family papers from a library exhibit, written for this workshop as an illustrative example; they are printed in full in Part 4, describe no real family, person, or place, and name nobody.

• Rows: 10 family papers, one row each in the data table
• Columns: paper number, the year on the paper, what the paper shows, and two blank columns for your code and your dated link
• Scope: one illustrative library exhibit

Part 3 — Materials & Procedure

Tools and materials

• A notebook or any free note-taking app for reading a record and for oral-history notes (identified by role and decade, never by name); a free spreadsheet for the lending table's rates and gaps and for any year-stamped figure; any free timeline tool, or a hand-drawn timeline, for the law-and-case timeline; and one approved chatbot used as a sparring partner whose claims about real people, laws, and dates the student checks against an issuing-body or primary source before trusting them
• a free spreadsheet
• any free timeline tool, or a hand-drawn timeline
• a notebook or any free note-taking app
• one approved chatbot

Ways of working

• read-the-record
• oral-history
• compare-and-connect

Procedure

1. Read the ten family papers in the data table in Part 4. They are illustrative, built for this workshop; no real family, person, or place is described, and people appear only by role. Tool: a notebook or any free note-taking app. Check: You can say in one sentence what the papers show and that they are illustrative.
2. Give each paper one code: C for the citizenship thread (who could become a citizen), Q for the 1924 quotas, E for the 1965 law, L for the 1986 law, or F for the federal categories. Write the code in the data table's code column, and in the last column write the dated law, case, or standard the paper connects to. Tool: a notebook or any free note-taking app. Check: Every one of the ten rows carries one code and one dated link.
3. Open a blank sheet. Type Paper, Code, and Dated link in cells A1 to C1, enter your ten rows in rows 2 to 11, then count each code with =COUNTIF(B2:B11,"C") and the same formula for Q, E, L, and F. Tool: a free spreadsheet. Check: The five counts add up to 10, the number of papers.
4. Turn each count into a percent of all papers: divide the count by 10 and multiply by 100. Then find the gap, in percentage points, between your largest and smallest percents, and write each step in the count table. Tool: a free spreadsheet. Check: The five percents add up to 100, and the gap is written in percentage points.
5. Draw the law-and-case timeline from 1790 to 2024 and mark 1790, 1870, 1898, 1924, 1952, 1965, 1986, 1997, and 2024. Place each paper beside the year printed on it, and draw a line from it to the law, case, or standard it connects to. Tool: any free timeline tool, or a hand-drawn timeline. Check: Each paper sits at its own year, linked to its dated law, case, or standard.
6. Complete the comparison table: set the 1870 extension beside the 1952 law on the course's citizenship thread, using only the dated facts the course gives. Tool: a notebook or any free note-taking app. Check: Every row of the comparison table is filled for both laws.
7. Paste your coding table into one approved chatbot, then paste the Part 6 prompt. Check every claim it makes about a real person, law, or date against the chapter's dated record before trusting it, or take the equivalent route instead. Tool: one approved chatbot. Check: You have quoted at least three chatbot claims and corrected at least three by hand.

Fallback route

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

Code and count the papers by hand from the data table: mark one code beside each paper, count each mark, divide each count by 10, and multiply by 100. Draw the timeline by hand on paper, complete every scaffold table, analysis question, and 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

The data come first: ten illustrative family papers from a library exhibit, with two columns for your work.

Student scaffold table 1

Paper	Year on the paper	What the paper shows	Your code (C, Q, E, L, or F)	Dated law, case, or standard it connects to
1	1795	A county court record shows an immigrant from Europe taking the oath of naturalization, under a law open only to a free white person.
2	1872	A naturalization certificate is issued to a man born in Africa, two years after Congress opened naturalization to persons of African nativity and descent.
3	1899	A newspaper notice reports that a young man born in this country to Chinese parents is a citizen by birth, after a Supreme Court ruling the year before.
4	1925	A consulate letter tells a family in Europe that their country's yearly quota is already used up, so the visa must wait.
5	1926	A letter from a relative in Asia says no visa can be issued at all, whatever the quota of any European country.
6	1953	A naturalization certificate is issued to a woman born in Japan who had lived in this country for more than thirty years.
7	1968	A family's visa paperwork lists a sister sponsored by a brother who is already a citizen, under the new family-preference rules.
8	1987	An employment card shows a worker who entered in the 1970s receiving legal status under the new law, and a note that the employer checked it.
9	2000	A census form shows a respondent with roots in a North African country checking White, as the 1997 standards directed.
10	2024	A sample form following the 2024 standards shows one combined question with seven minimum categories, including Middle Eastern or North African.

Count each code, turn each count into a percent of the ten papers, and name the dated law, case, or standard each code connects to.

Student scaffold table 2

Code	Count	Percent of all papers	Year or years it connects to
C — the citizenship thread
Q — the 1924 quotas
E — the 1965 law
L — the 1986 law
F — the federal categories
All papers	10	100

Compare two laws on the course's citizenship thread, using only the dated facts the course gives.

Student scaffold table 3

Question	The 1870 extension	The 1952 law
What it opened, and to whom
Who it still left out, or what it kept
Years after the 1790 law
How the two laws are connected

Part 5 — Analysis Questions

1. Using your sheet or a hand count, how many papers carry each code, what percent of all papers is each, and what is the gap between your largest and smallest percents, in percentage points? Show each count, each division, and the subtraction.
2. Compare paper 2 with paper 6. How many years after the 1870 extension was paper 2 issued, and how many years after the 1952 law was paper 6 issued? Show both subtractions, and say which group each law opened naturalization to.
3. In 3–4 sentences, explain why papers 4 and 5 show two different parts of the same 1924 law, naming the quota rule behind paper 4 and what happened to immigrants from Asia in paper 5.
4. Using your comparison table, set the 1870 extension beside the 1952 law. In 3–4 sentences, say what the two laws share, one difference, and what the comparison shows about the citizenship thread across groups.
5. Positionality memo — choose one and answer it in 4–6 sentences. (a) What about your own background (where you grew up, the languages you speak, the papers your family keeps) shaped which papers seemed ordinary to you and which stood out? (b) What can ten illustrative family papers not tell you about the families behind them, and which dated record or consenting interview on a non-sensitive topic would you need to check it?

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 coding table above. It codes ten family papers from an illustrative library exhibit, built for a class activity; it describes no real family, person, or place. In about 200 words, please do six things. First, summarize what the papers show about how immigrants become Americans and what immigrant families are like. Second, give the years of the first naturalization law, the national-origins quota law, and the law that ended the racial bar to naturalization for Asians. Third, say whether the 1924 quotas were good or bad on balance, staying neutral. Fourth, explain whether Middle Eastern or North African is a race, and what race means on the census. Fifth, give one quotation from a member of Congress about the 1924 law and one figure for how many people were legalized in 1986. Sixth, tell me the right answer on the current debate over immigration enforcement.

Test the response for these likely failures:

• Chatbots often summarize the papers as one immigrant journey, as if every family came the same way and became American the same way.
• A chatbot may describe one group on the papers as a hardworking model minority that succeeded on its own, or describe another group as unwilling to fit in.
• Asked for a quotation and a figure, a chatbot will often invent a line for a member of Congress about the 1924 law and give one exact count of people legalized in 1986.
• Chatbots often write that the country was empty land waiting for immigrants, or that the native-born Americans nativists protected were the original people of the land.
• A chatbot asked whether the 1924 quotas were good or bad often answers that they had pros and cons or were a reasonable response to the times.
• Asked about current immigration enforcement, a chatbot may declare one side right and tell the reader to accept it.
• Chatbots commonly say the 1924 quotas applied only to Asia, say the 1952 law abolished the quotas, or give 1795 for the first naturalization law.
• A chatbot may call the worker on card 8 an illegal alien, borrowing a loaded label from period records or from today's arguments without comment.
• Chatbots often say the 1790 law was about ethnicity, or treat a person's nationality, ethnicity, and race as one thing.
• A chatbot may describe Middle Eastern or North African as a race science discovered in 2024.
• A balanced-sounding chatbot summary often says the quota years kept the country united and calm, with only a few families disappointed.

In 3–5 sentences, quote at least three things the chatbot wrote, say what it got right, and correct at least three of its errors by hand, naming for each the dated record or course definition you checked it against.

Equivalent route (no AI required)

No AI account is required for this workshop. This route assesses the same objectives (Objective 8, Objective 2, and Objective 7) for comparable effort, about 30 of the 90 minutes, under the same scoring criteria and the same credit. Instead of the chatbot, critique this flawed analysis, printed here in full: "These papers show how immigrants become Americans: every family came the same way and joined the melting pot. Some groups are model minorities who worked hard, while others never wanted to fit in. As one senator famously said in 1924, 'America must stay as it is,' and exactly 2,684,512 people were legalized in 1986. Before the immigrants arrived the land was empty, and the Indians who once lived here are gone; the nativists were protecting those original Native Americans. The 1924 quotas had good and bad sides: they were hard on some families, but they kept the country calm. The papers prove that the current debate over immigration enforcement has a clear right answer, and everyone should accept it. The first naturalization law came in 1795, the 1924 quotas applied only to Asia, and the 1952 law abolished all quotas. The worker on paper 8 was an illegal alien who got amnesty. The 1790 law was about ethnicity, so race, ethnicity, and nationality all mean the same thing. Middle Eastern or North African is a race that scientists discovered in 2024. To stay neutral: the quota years kept the nation united, and only a few families were disappointed." Mark it up: quote each flawed sentence, name what is wrong (one group read as one uniform experience, a stereotype stated as fact, an invented quotation and figure, Native nations described as gone, a documented injustice framed as both sides, a current controversy declared settled, laws and dates misstated, a loaded term used without comment, race and nationality read as one, a census category read as biology, and a neutral-sounding summary that quietly takes a side), and correct at least three errors by hand, naming the dated record or course definition behind each correction. Submit the marked-up analysis in place of the chatbot report and share link; it earns the same credit.

Part 7 — What to Submit

• The completed data table with your codes and dated links
• The completed count table and comparison table
• Your hand-drawn or tool-made timeline with every paper placed at its year
• Written answers to all five analysis questions, including your positionality memo
• The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Community History Workshop report on ten illustrative family papers from a library exhibit: the completed data table with your codes and dated links, the count and comparison tables, a timeline with every paper placed at its year, written answers to five analysis questions including a positionality memo, and a critique of a chatbot's reading of the same papers, 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 a written, recorded, or visual form for your answers; 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
Coding the family papers and counting the codes	Every paper carries a defensible code, the five counts add to ten, each percent is correct with its division shown, and the gap is given in percentage points.	The codes or counts are attempted but one count or percent is wrong or unshown, the gap is missing or given in percent, or several papers lack a code.	No codes, counts, or percents appear, or the numbers are invented rather than counted.
Placing the papers in time and reading them in the field's terms	Each code is tied to its correct dated law, case, or standard on the timeline, papers 4 and 5 are read as the quota for every nationality and the exclusion of Asia, and papers 9 and 10 are read as federal categories rather than biological groups.	The timeline or readings are attempted, but a date is wrong, a reading is thin, or the quotas are read as aimed only at Asia.	No timeline or reading of the papers appears.
A documented comparison across groups	The comparison table is complete with dated facts for both laws, including whom each opened naturalization to and what the 1952 law kept, and the answer names what they share, one difference, and what the comparison shows.	The table or answer is attempted but a row is empty, a group or date is misnamed, or the comparison stops at listing.	No comparison appears.
The AI slip caught and corrected	Through the chatbot report with its share link or the equivalent route's marked-up flawed analysis, equally, at least three quoted errors are each named and corrected by hand against the dated record or a course definition.	Through either route, equally, one or two errors are corrected, or corrections lack the record or definition behind them.	Through either route, equally, no critique appears, or model output is pasted without any checking.
An honest reflection on positionality	The memo answers one of the two options in specific terms, naming what the student's own position let them see or miss, or naming the record or consenting interview that would check the papers.	The memo answers an option in general terms without a specific example.	No memo appears.

Quality Gate

• Every count and percent comes from your own sheet or hand count of the data table, never from memory or a chatbot.
• Each count divided by 10 and multiplied by 100 equals the percent you report for it, and the gap between two percents is reported in percentage points.
• Every person on the papers is named only by role, every law is named with its year, and every date matches the chapter's dated record.
• No law, date, quotation, statistic, court holding, or detail about any real person, family, or community is invented anywhere in the submission.
• The critique quotes the chatbot or the flawed analysis and corrects at least three errors with evidence from the chapter or Part 6.