How Database ID Patterns Work
There has been an interesting theory spreading across the election integrity universe that we felt needed some grounding in reality. It has to do with recognizing patterns, or the absence of patterns within voter ID’s across a state. The primary thing to remember when deciding whether claims like these have merit is Occam’s Razor: The simplest explanation is usually the correct one. The claim centers around the idea that there is a hidden algorithm within state voter ID’s that prove there is some type of fraud taking place. I love a good conspiracy as much as anybody, but this is not a smoking gun. There are enough factually identifiable flaws within our election systems that wild ideas like this detract from making substantive changes to the process that would lead to better transparency and improvement of the systems. This claim is rooted in a basic misunderstanding of how ID assignment in a working database is handled, in particular one that has been subject to complete data migrations between older and newer systems. Below is an explanation of how ID’s are assigned and the relation between sequential ID’s can shift over time.
When a database is first built, or an old database is migrated into a new system, all existing records are imported at once and given clean, sequential IDs. Any records added or changed after that point will naturally fall outside the original pattern because they were created at a different time. It is how every modern database works, no flaw, hidden algorithm, or evidence of fraud on it's own.
Old system: records exist with legacy IDs
All records imported into the new system at once
Real life continues, new registrations and changes are added
What is actually happening: IDs 001–890 were assigned in one automated batch on migration day. IDs 891+ were assigned one at a time, on different days, by different county offices, as normal life events occurred. There is no hidden pattern. There is a calendar.
Company starts with one salesperson: Alex
Two more salespeople join: Beth & Carlos
Nothing is missing. Beth used 1006 and 1009. Carlos used 1007 and 1010. The gaps in Alex's sequence are simply other people doing their jobs. Filtering to one person and calling the gaps suspicious is the same flawed logic.
Store launches with an existing product catalog
New products and seasonal items are added over time
The Bottom Line applies to every example above
Any living database will show a clear, orderly pattern among its earliest IDs that is the migration batch created all at once during a single process, or the original inputs. After that point, IDs are assigned one at a time as real events occur: new people register, employees join, products are added. Those later IDs do not follow the original bulk pattern, because they were never part of it.
Calling this a "hidden algorithm" is like noticing that the area code 479 covers northwest Arkansas, 480 covers the East Valley in Arizona, and 481 is in Houston. They werent partitioned and reserved in sequential state order from the beginning They were added later as the need arose. The numbers reflect reality. That is the entire explanation.