Clues into the Past: How to Do FAN Club Research
Introduction
When researching ancestors who lived in earlier time periods or regions with few records, the lack of records can create a brick wall in the research. This necessitates expanding the research to the cluster of people connected with the ancestor: immediate and extended family members, friends, associates, and neighbors, also known as the ancestor’s FAN Club.
Cluster research pieces together additional records and evidence that can overcome the brick wall. Cluster research leads the researcher to additional documents which may name the ancestor or provide indirect evidence that can overcome the brick wall. This article addresses when to use cluster research, who is in the ancestor’s cluster, how to organize the findings, and the steps for cluster research.
Deciding When to Use Cluster Research
Some of the research challenges that benefit from cluster research include the following:
Researching in time periods or locations with few records, such as pre-1850 or in burned counties
Identifying a female ancestor whose maiden name is not known
Distinguishing the identities of two people with the same name
Determining the place of origin or an earlier residence of an ancestor who migrated
Each of these research situations typically requires indirect evidence, which can be identified through cluster analysis.
Researching an ancestor’s cluster is time-consuming, so before beginning extensive research, determine a narrowly focused research question and review previous research to find any missing clues.
Next, create a timeline based on the ancestor’s research log, to summarize all known events and details. A timeline helps illustrate the gaps in the records and possible locations to search for those records. Since new records are added online on a regular basis, a record that was not located in a previous search may be available now. After thoroughly searching records for the ancestor, then begin cluster research.
Identifying Members of an Ancestor’s Cluster
Anyone named in the ancestor’s records is part of his or her cluster. “Family” in the FAN acronym is composed of three groups of people: immediate family, extended family, and others with the same or similar surname who lived in the same area. The ancestor’s immediate family consists of spouses, children, and stepchildren. Researching the extended family starts with the ancestor’s parents, siblings, in-laws, grandparents, aunts, uncles, and step-relatives, and expands from there. DNA research can help identify more members of the immediate or extended family.
Other families with the same or a similar surname who lived near the ancestor may be relatives, especially when the surname is not common. Start with people with the same surname who lived in the same area of the town or county. Before extending the surname search further out, research the ancestor’s immediate and extended family members, associates, and neighbors. Begin the surname study in census, vital, probate, and land records, and then widen the search to other records available for that region and time period, like city directories and tax lists.
“Associates” in the FAN Club interacted with the ancestor but are not identified as relatives. Examples of associates include witnesses at a wedding, informants for a death certificate, and executors and others listed in probate records, such as debtors. Other associates include signers of affidavits for military pension or bounty land applications, coworkers, and individuals doing business in land records, militia groups, immigration records, church records, or court documents. Two reasons justify the effort spent researching associates:
They may turn out to be family members
They may provide context and indirect evidence which uniquely identifies the ancestor.
FAN Club “Neighbors” lived near the ancestor. Census schedules, city directories, tax records, and land records may name the ancestor’s neighbors. Due to the high number of possible neighbors for each ancestor, focus on close or known neighbors first.
Organizing Cluster Research Findings
The amount of research that needs to be tracked increases significantly when it extends beyond a person’s immediate family. Keep records organized and searchable to make cluster research more manageable and effective. Two important organizational tools for tracking cluster research are a research log and the ancestor’s timeline.
Research Logs
Use a research log to record the names and details in each record found as well as all searches performed, . Keeping a log saves time in the long run, especially when it is digital and searchable. Research logs are more workable when they are narrow in scope, such as for an immediate family.
Record all details in the research log: occupations, military service, signature, physical features, locations, other individuals (FAN Club) named in a record. List any clues that could identify an ancestor’s economic standing, including the amount of land owned or taxes owed, to help confirm his or her identity in other records.
View original records when possible. They can reveal other details to distinguish the ancestor, such as signatures or the original order of a list. When a list is alphabetized, the community context is lost. For example, tax lists or petitions may have been compiled by neighborhoods, cemetery records may show family plots, and ship lists can reveal people traveling together. Community context is especially important for cluster research.
Create a folder for FAN Club research inside the ancestor’s research folder. As a new research log is created for a FAN Club individual or family being researched, save that research log in the FAN Club folder. If a family tie is found between the ancestor and a member of the FAN Club, a new “individual” folder should be created under the relevant “surname” folder so that the log may be moved.
Timelines
Chronological timelines summarize the research recorded in the logs and are especially critical for cluster research. Creating a timeline in Microsoft Excel (or other spreadsheet software) facilitates the analysis of expansive amounts of information and allows sorting on multiple columns. Excel’s search function can highlight all individuals with the same name.
Before starting cluster research, create a timeline to note all events and details in the ancestor’s life. Include information for extended family, associates, and neighbors by adding four columns to the spreadsheet: Known Extended Family, Possible Extended Family, Associates & Neighbors, and Role in Document. (See figure 3.) To maintain the ability to sort each column, avoid creating merged cells. When someone in the ancestor’s FAN Club is identified as an extended family member or has a significant number of records, create a separate research log and timeline for that individual.
The Cluster Research Process
Cluster research is an iterative process, meaning researchers need to cycle through repeated steps and refine the research plan as research unfolds and leads to new records with new information. As genealogists gain more experience with researching the FAN Club, knowing how extensively to apply a step and when to cycle back through the steps becomes more intuitive.
Step 1: Understand the locations where the ancestor lived
Study the locations and jurisdictions where the ancestor lived and learn what records are available for that time period. The FamilySearch Research Wiki is a helpful place to start. Understand the county boundaries of the location by using the Newberry Library’s “Atlas of Historical County Boundaries.” If the ancestor lived there before the boundary changed, search in the parent county. Sometimes duplicate records were made for the new county. Search online using the terms “historical maps” and the location to obtain additional information about the area. County histories may identify the places of worship within a reasonable proximity to the ancestor.
Step 2: Add persons named in the ancestor’s records to the timeline
Begin at the top of the timeline and add family members, associates, and close neighbors named in the ancestor’s records. Include all details that may serve as unique identifiers for the FAN individuals, such as their role in the document, occupation, literacy, and economic indicators. Include a theory for each person’s relationship with the ancestor: uncle, friend, church member. Family naming patterns can provide indirect evidence. A middle name could be a mother’s maiden name, or a pattern of names could match a possible extended family. For records that include neighbors—censuses, city directories, tax records, land records—start with adding just the names of known associates, rather than large numbers of neighbors, to the ancestor’s timeline.
Step 3: Prioritize the research order of family, associates, and neighbors in the timeline
Prioritize the research list based on how frequently individuals appear in the ancestor’s timeline and how strongly connected their roles are. For example, a witness at a wedding is more likely to be related than the judge who married the couple. Consider if the information is reliable. An extended family listed in an unsourced family tree might not be accurate.
After the immediate family, the extended family should be the next FAN Club priority because their records are likely to mention the ancestor’s unknown relatives. Next, list the associates and neighbors the ancestor had frequent interactions with, such as a neighbor who shows up in a census in Virginia and then Kentucky. This individual could be a relative, a close friend, or a member of the same church or ethnic group.
As cluster research produces new records with new names to consider, search the records that name neighbors for the new names. If the initial iteration of cluster research fails to answer the research question, add to the list of neighbors by recording around fifteen families listed on each side of the ancestor in census or other records of the neighborhood.
Step 4: Research the prioritized list and revise the priorities as evidence is analyzed
Research starting at the top of the prioritized list and record direct and indirect evidence in the FAN Club research log for that individual. Re-analyze the frequency and strength of connections based on new records and adjust the prioritized list accordingly. The following examples demonstrate cluster research methodology.
Migration.
Prior to the early 1900s when transportation options increased, people often migrated with relatives or friends or followed each other to a new location. Sometimes their traveling companions were extended family members and at other times they belonged to the same ethnic or religious group. When an ancestor’s possible prior location shows the same pattern of FAN names as the new location, this continuity provides indirect evidence for the prior location. Figure 5 is an 1830 land ownership map for Trumbull County, Ohio, showing Thomas Pauley living next to E. Cowdery. Thomas Pauley signed the marriage license for Robert McCormick’s daughter, Rebecca, when she married Erastus Cowdery, after her husband, James Pauley, died. Both Thomas Pauley and Robert McCormick lived in Northumberland County, Pennsylvania, as shown on Robert McCormick’s timeline in Figure 3. By researching Robert McCormick’s FAN club, a possible location for James Pauley’s parents was identified
Immigration. Emigrants usually traveled with relatives, neighbors, or their church or social group. They often settled in areas with people who spoke their language or shared their cultural background. If the researcher cannot find an immigrant’s town of origin or passenger list, searching for the ancestor’s FAN Club in immigration and other records might produce clues to his or her extended family or hometown.
Maiden name for a female ancestor. Ancestors often interacted with their associates and neighbors, which could lead to them marrying one of their children or a sibling. Research individuals in the ancestor’s census household with a different surname. Another approach is to find the husband in a post-1840 census just before he married. Search for women with the correct first name and of the right age who lived in the same or nearby town or county. Check whether they disappeared from the census about the time of marriage. Prior to 1850, look for families who lived nearby with a female age 15-29.
When a man received land for an unusually small amount of money or a token (like an ear of corn) from someone with a different surname, that person may have been a member of his wife’s family. Cemetery records that show plot layouts can provide FAN names to research because family members were often buried near each other. If a woman was single or widowed, a male relative may have appeared for her in court as a witness or in another role. Using one of these cluster methods or a combination of them may lead to evidence of the missing maiden name.
Same name or common surname research. Distinguishing the identities of multiple people with the same name or researching individuals with a common surname, such as Smith, presents extra research challenges. Recording each identifying detail helps with this research. Since every person’s FAN Club is unique, it can be used to identify which individual was named in a particular record and to separate identities.
Step 4: Write proof arguments for the ancestor
Sometimes researching the FAN Club leads to records that directly state the needed information. However, cluster research usually produces indirect evidence, which needs to be combined to support conclusions. Any indirect evidence or conflicting evidence should be summarized and resolved in a proof argument, “a detailed, written explanation of the evidence and reasoning used to reach a genealogical conclusion.”
Here is an example:
Research Question: What was the maiden name of Sally who was listed as Samuel Combest’s wife in his 1844 Pulaski County, Kentucky, will?
1. Sally [Ancestor] was listed as the wife of Samuel Combest [FAN Family] in his 1844 Pulaski County, Kentucky, will.
2. Samuel and Sally Combest’s ten children [FAN Family] are named in his will and in a note inserted in the Samuel D. Combest family bible. Three of them were
John Combest
Margaret Combest
Samuel Dick Combest
3. The 1803 tax list for Pulaski County shows that Samuel Combest and John Dick both lived on Fishing Creek. [FAN Neighbor]
4. An 1841 pension file for Margaret Dick of Pulaski County, widow of John Dick, includes a page from the family bible showing Sarah Dick’s birth in 1778.
When considered alone, the above items of information do not prove that Sally Combest’s maiden name was Dick. Researching Sarah’s FAN Club, however, identified records that contain indirect evidence of her maiden name.
Conclusion
The nature of genealogy research brings most researchers to a part of their pedigree that lacks the records needed to prove the next relationship. Researching an ancestor’s cluster of family, friends, associates, and neighbors leads to additional records with new evidence. Applying cluster genealogy techniques in an iterative research process unlocks the path to discovering missing ancestors.