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Between the Lines

The Temptation to Assume in Genealogy

There is a moment in almost every genealogy project when temptation shows up. It does not usually sound reckless. It sounds reasonable. It sounds efficient. It often arrives as a single sentence: “This must be the same person.” That sentence has damaged more family trees than missing records ever could, because it pushes the story forward without proof, and it does it in a way that feels productive.

Assumptions feel helpful because they fill the quiet places. When the paper trail goes thin, your mind wants to keep moving. You want to connect the last solid record to the next solid record, and you want the line between them to be clean. The trouble is that assumptions do not age well. They harden into “facts” through repetition, and once other conclusions are built on top of them, the mistake becomes difficult to remove without rebuilding the whole section of the tree.


Most wrong turns in genealogy are not caused by bad intentions. They are caused by good intentions and incomplete testing. A researcher sees a record that looks close enough, and the brain treats it like confirmation. A marriage record with the right name and the right decade. A man with the same name in a neighboring county. A military file that seems to match the age. A land deed with a familiar sounding place name. One attachment is made, then the rest of the story starts building itself around that attachment. The gap looks solved, but it is only covered over.

The most common assumption follows a pattern that feels tidy. Same name, close age, same general area, therefore the same person. That logic sounds clean, but it is incomplete. Names repeat constantly, especially in the nineteenth century, and especially in communities where the same given names are reused across generations. There can be two, three, or five men with the same name living within a short distance of each other, sometimes all at once. When a name is common, the burden of proof goes up, not down.

A wrong identity does not stay contained. It multiplies. A wrong marriage creates the wrong children. The wrong children create the wrong descendants. Then the error spreads because someone else copies the tree, and after a while the mistake looks “established” simply because it appears in many places. Repetition does not create truth. It only creates confidence.

Some assumptions are especially tempting because they feel meaningful. The story lines up with a big historical event, and that event seems to explain everything. A war that explains missing years. A migration wave that explains a move. A tragedy that explains a sudden change in household. Those are powerful narratives, and that is why they are risky. A strong story can make a weak conclusion feel solid.

The discipline you want in genealogy is not about being negative. It is about being careful with what you claim. If the records do not support an explanation, the responsible answer is to leave it open and clearly unknown. That is hard, because it feels unfinished, but unfinished is often the honest result.

Being stuck is not failure. Being stuck is accuracy doing its job. A gap is not an invitation to invent. It is a warning sign that says, “Past this point, the records are not protecting you.” Beyond that point, your methods matter more than your momentum.

Here is a habit that prevents most bad attachments. When you feel tempted to assume, write the idea down separately and label it as a question, not as a conclusion. Write it in a way that keeps you honest. “What if this is the same person.” “What if this marriage belongs to my line.” “What if this explains the move.” A question keeps the door open for evidence. An assumption closes the door and makes you defend it.

When you are deciding whether two records belong to the same person, you do not want one perfect clue. You want several ordinary clues that keep agreeing with each other. Think of it as building a profile, not matching a name.

Start with place. Do not stop at the state. Get down to the county, township, and neighborhood when possible. Track whether the person stays in the same cluster of households across time.

Then look at people. Neighbors, witnesses, in laws, and recurring associates often tell you more than a matching surname does. If the same set of names keeps appearing near your person, that consistency matters.

Then check time. Ages will wobble, but they should wobble in a believable way. If one record implies a birth year of about 1830 and the next implies 1820 with no reason, that is a warning, not a small error to ignore.

Then look for continuity in the paper trail. Taxes, deeds, court minutes, and probate items can anchor a person year by year. These records are often better than census alone for proving presence in a specific community.

Then compare the smaller details. Occupation, property value patterns, literacy marks, and birthplaces across multiple censuses can help separate two men with the same name.

Finally, handle missing evidence carefully. A missing record only means something if you know the record set is complete and reliable for that exact place and time. Otherwise, the absence may be about loss, poor record keeping, or indexing problems, not about the person.

If those details keep agreeing, you can begin forming a strong identity case. If they conflict, treat that conflict as a useful signal, because it may be telling you that you are looking at two different people who share a name.

If you want a quick way to keep yourself honest, say this out loud while you work. “I am not proving that this record could fit. I am proving that it must fit better than any other option.” That single shift changes the quality of the work. It turns genealogy from story building into evidence building.

In the end, the goal is not a tree that feels complete. The goal is a tree you can defend. That means accepting uncertainty when uncertainty is what the evidence gives. It means resisting tidy endings when tidy endings require guesses. It means valuing restraint as much as discovery, because restraint is what keeps your research stable over time.