For many years I have served as a volunteer for National History Day (NHD). NHD began in Cleveland in 1974 with students participating in the equivalent of a Science Fair for history. Participants develop research questions, conduct research, analyze information, and write conclusions based on a theme that changes annually. The originator, David Van Tassel, hoped to help younger students see the relevance of history in their lives. By 1976 the competition spread statewide and within four years it was nationwide. Currently, around 500,000 students participate each year, supported by 30,000 teachers. Students may participate in NHD at local, regional, state, and national levels. The strongest projects advance throughout the levels. Students choose to participate individually or in a group. Individuals submit papers, websites, documentaries, performances, or exhibits. Groups can submit websites, documentaries, performances, or exhibits. You can view examples here.
My daughter dove into history day in 8th grade and in 10th grade represented Washington State at the national contest in Maryland. As a History Day parent, I provided transportation and the occasional feedback upon request. Significant adult help is forbidden. I served as a chaperone for the national competition. Imagine a college taken over by hundreds of students excited about history, some of them wandering around in costume for their performances, and all cheering their state team. About ten years ago I first volunteered as a judge. Judges receive an orientation to the rules and processes of the contest and use rubrics to rank the projects in teams.
For the last couple of years I’ve participate virtually as a judge. I’ve judged documentaries and websites from home. Every year I learn from each of the thirteen or so student projects I review. This year’s theme is “Debate & Diplomacy in History: Successes, Failures, Consequences.” The creativity of the students amazes me. They locate primary documents, interview experts, communicate their thesis, and analyze their findings. The skills they learn through NHD will aid them in future endeavours.
If you are interested in volunteering, you can find the organization in your state by checking out the affiliate links. I’m so grateful for these students who teach me, fill me with hope, and inspire me.
Like any avid family history researcher or professional genealogist, I had known for years that the 1950 US census would be released on 1 April 2022. As the release date drew near, the number of articles, presentations, and blog posts about the 1950 census grew exponentially. Many people prepared to spend hours searching for their families starting at the stroke of midnight. I wasn’t among them. Why? I anticipated the website crashing under the weight of so many people trying to access the database. I might also have decided to go against the grain and not get caught up in the drama. Part of me wanted to learn from everyone else who went first. What I learned was that it was a rousing success so I set aside some time this morning to explore.
Background on the 1950 census
The 1950 census is the first census to be released with Machine Learning and Artificial Intelligence technology. A machine reviewed the census and created a searchable database of names based on interpretation of handwriting. That’s amazing! It’s a far cry from the days of using the Soundex and microfilm in a dark room at the National Archives poring over faded copies for hours. It’s not quite what researchers have become accustomed to: a census that is indexed and easily searchable on more than one website. That’s coming soon.
Based on early ideas about using the 1950 census, I was prepared to spend hours looking for the Enumeration District (ED) where I thought my family might be. The machine-derived index made that irrelevant for my first searches. The index will be updated with human effort over the upcoming months. Indexes for the first two states, Wyoming and Delaware, have been released at MyHeritage. Ancestry and FamilySearch also have the images available and are working on indexing. Each company has unique search capability and index. Whenever you can’t find your family in an index, before giving up or resorting to reading each page, check an index at a different website.
For the machine-derived index, keep in mind that enumerators recorded information by household. Typically, the surname appears next to the head of the household and usually a straight line or nothing is written for subsequent family members of the same surname. That meant I wouldn’t be looking for my father and mother who were children at the time. I would be searching for my grandfathers.
The challenge: How long would it take to find my parents?
The two surnames I was searching for, Davis and Johnson, are incredibly common and my family wasn’t living in rural or remote areas in 1950. I was prepared to slog my way through reading many pages before I found them. Before I began, I reviewed a useful article by Teresa Koch-Bostic which is available for members of the National Genealogical Society. Then I started my timer.
Finding Dad: 9 minutes and 26 seconds
Here are my steps and what I found:
I reviewed my father’s timeline from my genealogy software, Reunion. I knew the family lived in Hollister, San Benito County, California. My dad graduated June 1952 from San Benito County High School.
I completed the information I had for state, county, and name, entering California, San Benito, Walt Davis (my grandfather’s name, the head of the household). I soon realized that Last Name, First Name order would be an improvement, but not crucial to success. I also noticed that the machine picked up the name David for Davis (see red arrow below), which is a good thing, since terminal letters in handwriting are often difficult to decipher. I switched my strategy and re-entered the name as Davis Walt. (His full name was Walton but he often went by Walt, and sometimes was confused with Walter, his father.)
I scrolled the results and the 26th name I encountered was my grandfather, Walton Davis. The family appeared on the bottom of page 1 and the top of page 2.
A close review of the page revealed the amount of information captured in the census. Although none of the information surprised me, seeing the names of my grandparents, uncle, and father, all gone now, made me smile. My grandmother’s stories of the auto dealership and garage sprang to mind and I could almost smell the oil and gas and see my grandfather disappointed with his challenges in receiving the type of cars he wanted to sell. I could picture my 16-year-old dad and his 17-year-old brother in coveralls with flat top haircuts, pumping gas and working in the garage.
My next step was to record the information in Reunion. The data entry took an additional 15 minutes because I created a new citation template for the 1950 census and added other useful information from the census to all the family member’s profiles. I updated my grandfather’s WikiTree biography and I will need to do the same for the rest of the family members.
Finding Mom: 1 minute and 47 seconds
I repeated the strategy for my mother, looking for my maternal grandfather, (in reverse order) “Johnson Lindell,” in Dyer County, Tennessee. Bingo! Six names down the list, there he was, along with his entire family (including my mother) at 420 Kist Avenue, the house I remember from my childhood (see arrow number 1, below). My great-uncle, his son and my great-grandmother all appear to be at the same house number, but I believe the second house was already on the property at that time. I’ll have to ask my uncle. My grandfather worked at the cotton mill down the street, as did my Aunt Earline, on line 22 (enumerated as Mildred E. Coleman.) A couple of their neighbors also worked at the mill. My great uncle A.W. (line 25, household 87) was delivering pottery. I grew up using the peach-shaped sugar bowl my mother received from his time driving the pottery truck.
Two family members appear in the supplemental information at the bottom of the page (arrow #2). The census used a sampling strategy and enumerators recorded additional information for every fifth person on the census. My uncle L.S. was on line 18 and my cousin Jimmy was on line 23. The corresponding lines in the bottom section show information about residence in past year, nativity of parents, schooling, work, income, and military service. The information for Uncle L.S. is interesting. He was 16 years old and the information indicates he had completed 4th grade and did attend school in 1950. He is over 14 but the next section is blank, when the section header indicates it should be filled out for anyone 14 or older. His enumeration data above on line 18 noted he was working, delivering papers. Jimmy was two, so the information for him isn’t very revealing. Important information may be here in other situations. It could be the impetus for searching military records, understanding the family’s social situation, or the key to discovering an immigration pattern.
My examples were simple cases. I knew the exactly where the families were living and both were reasonably-sized communities. I knew the address of one place but I didn’t need it. If I were doing research on a family that relocated often and was in an urban setting, my results would have been different.
I’m looking forward to catching up on other family members in 1950. I don’t have any burning questions right now about my family in that time period, so it’s likely I will coordinate gathering 1950 census information as I improve the biographies of my family on WikiTree. And the data might be important for upcoming client work. I’m glad I took the few short minutes to explore the 1950 census. I’ll be back soon!
Genealogists commonly encounter errors in census data. But what about the deliberate misuse of census data to cause harm? The 1840 census illustrates how census data were used for ill.
Family historians rely on information from census records, hoping to identify family units and to trace location and situation over time. The 1840 census, like those from 1790 to 1830, documented families under the name of the head of household and counted other household members by age, gender, race, and status of free or enslaved. The informant was unknown and could be the enumerator, a neighbour, or any member of the family. Over time, the data collected for each census varied, depending on the priorities of the government. Data from the first census in 1790 determined Congressional representation and funding for the new government.
As the government’s need for information grew, the census data accommodated that need. By 1820, naturalization status and involvement in agriculture, manufacturing or trade were assessed. Collection of information about health or functional status began in 1830 with enumeration of those who were deaf, deaf mute, or blind. In 1840, the enumeration included those insane (referring to people with mental illness) or idiotic (referring to those with developmental or intellectual disabilities) and if they were supported by private or public means.
As any family historian knows, the information in the census can be flawed at the individual level. The misinformation may have occurred at the time of enumeration, with ages guessed, misstated, or misunderstood. Location information is primary and most reliable, since the enumerator went from dwelling-to-dwelling collecting information. Errors could be introduced during transcription since each enumerator created multiple copies. Fraud by the enumerator was also a possibility. Data were recorded across large sheets in columns. Standardized forms introduced in 1830 improved collection of census data.
Congressional reports collated census data to inform policy, and the 1840 census was no exception. The Compendium of the Enumeration of the Inhabitants and Statistics of the United States, as Obtained at the Department of State, from Returns of the Sixth Census supported arguments of politicians in slaveholding states because it reported that the percentage of “colored persons” who were “insane and idiots” was higher in northern states compared to southern states. The statistics showed that “the negroes and mulattoes of the north produced one lunatic or idiot for every one hundred and forty-four persons, while the same class at the south produced only one lunatic or idiot for every fifteen hundred and fifty-eighth.” Politicians like Senator and former Vice President John C. Calhoun of South Carolina claimed that slavery benefited “the African race.” In an 1837 speech he said, “I may say, with truth, that in few countries so much is left to the share of the labourer [referring to enslaved people], and so little exacted from him, or where there is more kind attention to him in sickness or infirmities of age.” The census bolstered Calhoun’s pro-slavery politics and his personal finances as an enslaver. The John C. Calhoun household in 1840 included seventy-seven enslaved people.
Dr. Edward Jarvis, a specialist in treating mental disorders, used the time he was convalescing from a broken leg to study the 1840 census records. Jarvis reviewed the entire census and recalculated the totals, noting multiple errors in the tallying of the data for free colored people. An example is the census of the community of Scarborough in Cumberland County, Maine. No free people of color were enumerated in Scarborough, but the totals include 6 “colored persons” who were classified as “idiots and insane” as shown in the image below.
Jarvis determined that the Worcester, Massachusetts enumeration contained a more flagrant error. The totals page, shown below, noted 133 “colored persons” who were insane or idiots and cared for at public expense. The entire “free colored” population shown on the prior page was 150. Dr. Jarvis’ investigation revealed that the 133 people were white residents of the state hospital for the insane.
Jarvis’ analysis became known to members of Congress and on 26 February 1844, John Quincy Adams brought a resolution to the House of Representatives that the “Secretary of State be directed to inform the House whether any gross errors have been discovered in the printed …census…[of 1840]…and, if so, how those errors originated, what they are, and what, if any, measures have been taken to rectify them.” On April 10 1844, John C. Calhoun was appointed Secretary of State and on 6 May 1844, he responded to the House Resolution of 26 February “stating that no such errors had been discovered.” Efforts to address the errors continued for decades, with Jarvis continuing to publish and refute publications that cited the erroneous data.
The 1840 census errors remain. John C. Calhoun used the results of the faulty census to justify slavery to the British government, who had pressured the United States to abolish slavery in Texas. A report in 1900 concluded that errors were present in 1840 and attributed the errors to “ineffectiveness of the machinery by which the census was then taken” including the amount of data being collected, inadequate compensation, and improper supervision. That these errors remain serve as a testament to people who would misuse data to further the ill treatment of other members of society, such as the enslavement of 2,487,355 people counted in the 1840 census. As family historians, our experience with individual errors can help us understand how the magnification of errors combined with nefarious political actions furthered the cause of enslavers and underpins myths that survive to this day.
 United States Department of Commerce, U.S. Census Bureau, Measuring America: The Decennial Censuses From 1790 to 2000, Report Number POL/02-MA(RV), September 2002, United States Census (https://www2.census.gov/library/publications/2002/dec/pol_02-ma.pdf : accessed 19 March 2022), p. 5-65.
 “The First U.S. Census is Taken,” Jeremy Norman’s HistoryofInformation.com (https://www.historyofinformation.com/detail.php?id=1347 : accessed 20 March 2022).
 U.S. Department of Commerce, Measuring America, September 2002, p. 5-7
 U.S. Department of Commerce, Measuring America, September 2002, p. 119.
 Tammy Hepps, “When Henry Silverstein Got Cold: Fraud in the 1920 Census,” Homestead Hebrews (https://homesteadhebrews.com/articles/when-henry-silverstein-got-cold/ : accessed 25 March 2022).
 U.S. Department of Commerce, Measuring America, September 2002, p. 5-65.
 Department of State, Compendium of the Enumeration of the Inhabitants and Statistics of the United States, As Obtained at the Department of State, from the Returns of the Sixth Census, (Washington: Thomas Allen, Printer, 1841); digital images, FamilySearch (https://www.familysearch.org/library/books/viewer/195136/ : accessed 19 March 2022).
 Edward Jarvis, Insanity among the Coloured Population of the Free States (extracted from the American Journal of the Medical Sciences for January, 1844, (Philadelphia: T.K & P.G. Collins, Printers, 1844), p. 6; digital images, Internet Archive (https://archive.org/details/101475758.nlm.nih.gov : accessed 20 March 2022).
 John C. Calhoun, Speeches of John C. Calhoun: Delivered in the Congress of the United States from 1811 to the Present Time, Chapter XIV, “Speech on the Reception of Abolition Petitions, February, 1837,” (New York: Harper & Brothers, 1843), p. 225; digital images, Internet Archive (https://archive.org/details/speechesofjohncc00incalh/page/224/mode/2up : accessed 19 March 2022).
 1840 U.S. Census, Pickens County, South Carolina, population schedule, Pickens District, p. 354 (stamped), John C. Calhoun household, line 12 (hand counted); digital images, FamilySearch (https://www.familysearch.org/ark:/61903/3:1:33S7-9YT5-9L1P and https://www.familysearch.org/ark:/61903/3:1:33SQ-GYT5-9PDH : accessed 20 March 2022).
 Robert W. Wood, Memorial of Edward Jarvis, MD, American Statistical Association, (Boston: T.R. Marvin and Son, Printers, 1885), p. 10-12; digital images, GoogleBooks (https://books.google.ca/books?id=amKMsWB1Jy8C : accessed 19 March 2022).
 Edward Jarvis, Insanity among the Coloured Population of the Free States (extracted from the American Journal of the Medical Sciences for January, 1844, (Philadelphia: T.K & P.G. Collins, Printers, 1844), p. 7.
 “Mr. ADAMS offered the following….,” Congressional Globe, U.S. House of Representatives, 28th Congress, 1st session, p. 323, col. 3; digital image, A Century of Lawmakingfor a New Nation: U.S. Congressional Documents and Debates, 177401875, (https://memory.loc.gov/cgi-bin/ampage?collId=llcg&fileName=013/llcg013.db&recNum=346 : accessed 20 March 2022.)
 Journal of the House of Representatives, Vol. 39, 6 May 1844; digital images (https://memory.loc.gov/cgi-bin/ampage?collId=llhj&fileName=039/llhj039.db&recNum=876&itemLink=D?hlaw:3:./ : accessed 20 March 2022)
 Albert Deutsch, “The First U.S. Census of the Insane (1840) and Its Use as Pro-Slavery Propaganda,” Bulletin of the History of Medicine, Vol. 15 (May 1944), p. 475; digital images JSTOR (https://www.jstor.org/stable/44446305 : accessed 19 March 2022).
 Peter Whoriskey, “The bogus U.S. census numbers showing slavery’s ‘wonderful influence’ on the enslaved,” The Washington Post, digital edition,17 October 2020, (https://www.washingtonpost.com/history/2020/10/17/1840-census-slavery-insanity/ : accessed 20 March 2022).
 Albert Deutsch, “The First U.S. Census of the Insane (1840) and Its Use as Pro-Slavery Propaganda,” Bulletin of the History of Medicine, Vol. 15 (May 1944), p. 477.
Carroll D. Wright, The History and Growth of the United States Census prepared for the Senate Committee on the Census, (Washington: Government Printing Office, 1900), p. 37; digital images, Census.gov (https://www.census.gov/history/pdf/wright-hunt.pdf : accessed 20 March 2022).
 Department of State, Compendium of the Enumeration of the Inhabitants and Statistics of the United States, (Washington: Thomas Allen, Printer, 1841), p. 368.
Every new project has a honeymoon period. There’s the anticipation of what might be discovered and the pleasure of setting up the project so that the research proceeds smoothly. Here’s a glimpse into my project set-up process.
A little over a year ago I started using Airtable as my research log. I have enough understanding of programming to be dangerous. I even took a class in Fortran in college and I learned how to use Microsoft Access when I worked in a health services research setting. I love relational databases even more than I love spreadsheets. Airtable is a “spreadsheet-database hybrid with features of a database but applied to a spreadsheet” according to Wikipedia. Nicole Dyer of Research Like a Pro (RLP) with FamilyLocket has shared terrific bases (templates) in the Airtable Universe. I developed my own adaptations to Nicole’s RLP with DNA Multiple Testers Base.
Below is a screenshot of the documentary research log I use based on Nicole’s template. I’ve grouped this log by surname (4th column), then sorted it by date of event (3rd column) then locality (5th column). Dates are written in YYYY-MM-DD format to sort the records (rows) by a field (column). Place names begin with the two-digit state abbreviation, followed by county, and town. This arrangement also supports sorting without creating multiple fields to sort. And if you are looking at column 8, yes, I do create the citations when I first look at the document. I have a citation template (also in Airtable).
Every project has a folder on my drive which is backed up to Dropbox. The folder organization varies by project. The snapshot below is for my mysterious 2x-great grandmother, Mattie Childress. Each research question has a numbered file. “00-Mattie death date” and “01-Parents for Mattie” are examples. Nested within the folder are sub-folders for phases of research. “Archive” holds prior drafts and will be discarded at the end of a project. “Analysis” contains tables for census or timeline analysis. “Images” has screenshots of diagrams.
I’ve used Google Docs and Sheets and struggle to use the filing system in Google Drive. Many people use them to good results. Using Google docs, sheets and drive allows sharing through links. I get around this by sharing Dropbox folders for large files.
File names for individual items (documents, images, spreadsheets) have evolved. There are two styles I use consistently: Name of document first or date first. When I am writing a report, the name of the document is written with underscores, then the date, always in YYYY-MM-DD format.
For sources (scans of originals, downloaded census, birth, marriage, death, etc.) I lead with the date, followed by the last name in caps, then location and type of record. I use dashes between elements of the date in YYYY-MM-DD format. This creates an instant timeline in my folders. Locations are organized from large geographic region to small.
I set up the project report using a template and “write as I go.” Writing the report while I’m working supports the analysis process and I’m not faced with a blank page at the end. When working on client projects, writing-as-I-go also helps me stay within hourly limits for a project. The template, like naming conventions, has evolved over time. I use a Microsoft Word .dotx file which includes sample paragraphs I often need (such as explaining the usages of different types of DNA tests or how autosomal DNA is used to predict relationships).
I started a new project two weeks ago and set it up as described here. I can spend a few minutes or several hours researching knowing that I can focus on the research and analysis. And I’m enjoying the honeymoon!
Family history research can be full of surprises. Have you ever been tempted to add a pet to your family tree? I came across Sebastian the Himalayan Cat while looking at a DNA match. (The match was to Sebastian’s human dad, not Sebastian!)
I have to say, Sebastian’s people are doing a good job on tree completeness! All sixteen 2x-great-grandparents of Sebastian are identified!
I use Reunion as my genealogy software. I’ve been a Mac user since the first Macs came out and Reunion has been with me for as long as I’ve been serious about family history research. I’ve been through many upgrades over the decades and somewhere along the line some new status buttons became available. I would have never thought of this status choice for a child.
And as you can see, Sebastian’s family is in good company, since Family Pet is also an option.
Stay tuned for further Oddities in future blog posts!