|Part of the series on|
“”You are not just wrong. You are wrong at every conceivable level of resolution. Zooming in on any part of your worldview finds beliefs exactly as wrong as your entire worldview.
|—There's a "de-motivator" poster for everything.|
Fractal wrongness is the state of being wrong at every conceivable scale of resolution. That is, from a distance, a fractally wrong person's worldview is incorrect; and furthermore, if you zoom in on any small part of that person's worldview, that part is just as wrong as the whole worldview.
 Dealing with the fractally wrong
Debating a person who is fractally wrong leads to infinite regress, as every refutation you make of that person's opinions will lead to a rejoinder, full of half-truths, leaps of poor logic, and outright lies, which requires just as much refutation to debunk as the first one—kind of like a nested Gish Gallop, where each point both surrounds and is surrounded by an equally wrong argument. It is worth noting that being fractally wrong can be handy for the losing side in a public debate, since you are likely to leave your opponent looking baffled and unable to deal with each level of wrongness.
While arguing with these people can be amusing at times, we suggest that if you ever get embroiled in a discussion with a fractally wrong person on the Internet—in mailing lists, newsgroups, or forums—your best bet is to say your piece once and ignore any replies, thus saving yourself time.
 “BUT IT FITS!”
- See also, shoehorning
Professor Stephen Law has written about a form of fractal wrongness he calls “BUT IT FITS!” (otherwise known as "of course 'they' WOULD do that"), in which a lack of evidence for a crank idea, or even evidence that directly contradicts it, can easily be turned on its head to support the same crank theory.
People who are believers in over-arching conspiracy theories often display traits of being fractally wrong, as every time you refute one of their points it can be turned into further evidence that "they" are suppressing the truth. In these cases, a complete lack of evidence for something is easily explained away as part of the conspiracy, and the lack of evidence for that is also nicely hidden. The same can be said of some believers in young earth creationism who view evidence contrary to their position as evidence of God testing their faith. There is no evidence that could be produced to convince such people that they may be wrong, and every level is nicely buffered against reality by more points in the fractal.
Law shows the problem with this kind of thinking when he tells the story of a man who believes dogs are alien spies from Venus. Any arguments his friends make as to why that can not be is turned around to work with the theory. For instance, when the man insists that there are transmitters in their brains his friends reply that transmitters have never been seen in dog brains. The man replies that the transmitters are "made of organic material indistinguishable from brain stuff", so they are well hidden.
This is also the tactic that dodgier fantasy and science fiction writers use to keep the plot together. It doesn't matter that you just found two dozen gaping holes in the storyline of Doctor Who; the show writers can easily pull something out of their asses to patch it right up.
Basically, “BUT IT FITS!” can be used to justify virtually anything.
 Consistent wrongness
The term "fractal wrongness" may also be used to refer to someone who is consistently wrong on nearly everything they predict or claim. Repeatedly failing predictions is one of the best ways of revealing fractal wrongness, because while an idiotic worldview may work in someone's head, it can be seen failing when actually put to the test. Hilariously, people who are consistently wrong tend to be quite confident in their position while championing it.
The expression appears to date from around October 2001 where it was used by then computer science student Keunwoo Lee in a lexicon of computing. The phrase is a metaphor deriving from the colloquial meaning of a fractal, which refers to an image which is substantially the same at any level of scale — in other words, it is impossible to determine how much the image is zoomed in simply by looking at it.
 See also
- Written by wildcardjack on Fark.com