If you abstract "non-function" as the thing that is meant to be demonstrated, then it surely is a Vorfuhreffekt (literal translation: demonstration effect). More formally, the Vorfuhreffekt is "I just observed X so I wanted to demonstrate it, but then while demonstrating it, X did not occur". Now just substitute X for "non-function" and resolve the double negations by DeMorgan's law.
I'm wondering whether the Vorfuhreffekt can be explained in terms of statistics, similar to regression to the mean. I.e. the observation that something worked or worked very well is often an outlier, so when repeating the experiment, one get a worse outcome in expectation. It is a kind of selection bias.
When you can't type the umlauts the correct way is using an additional e after the vowel, like this: Vorfuehreffekt. One more example: "schoen" instead of "schön" and not "schon".
Vorfuhreffekt is different and just sounds wrong. The German ear tries to understand this like this: "the effect of having gone ahead", but in German you don't conjugate substantives, so using the past of "fahren" ("fuhr") doesn't work here. This is irritating, at least for me.
For "schön" and "schon" however it does really matter because these words are in English "beautiful" and "already".
I just realized that my post could be interpreted as suggesting that I personally had immigrated to the U.S. from Germany. In fact, my grandfather did. But the two-syllable interpretation has affected every subsequent generation.
I've been thinking patience might play a role; I had this issue often as a kid.
When you have a computer problem and do some things to fix them, it doesn't work, you call a parent over and they do exactly the same thing and it does work... hm.
Maybe the computer was just stressed by my constant attempts and clicking and going away for a short time gave the system time to sort its internals and be ready for input again? shrug (a kid's reasoning)
I'm wondering whether the Vorfuhreffekt can be explained in terms of statistics, similar to regression to the mean. I.e. the observation that something worked or worked very well is often an outlier, so when repeating the experiment, one get a worse outcome in expectation. It is a kind of selection bias.