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Of course, proving a model wrong is an important accomplishment in itself [25], but we felt that not providing an alternative would have been unsatisfactory on many levels.
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That may well be true, but what this model gets wrong is that algorithms aren't crafts.
Those who consistently point to John F. Kennedy's Moon Speech of 1961 and the success of the Apollo program, and argue that the U.S. should use this as a model are wrong and are sadly stuck in their childhood.
The idea that the best models never fit all the data was summed up 30 years ago by the statistician George Box when he said, 'all models are wrong; some are useful' [ 2].
Box's [30] famous dictum that while all models are wrong, some are still useful, certainly applies.
In 1976, a British statistician named George Box wrote the famous line, "All models are wrong, some are useful".
We fall back on the axiom: all models are wrong; some are useful [ 52].
But do not despair, for while 'essentially, all models are wrong, some are useful' [ 47].
The disadvantage is that if the polls are wrong, the model will be wrong too.
It is often said that "all models are wrong, but some are useful" [ 60].
But those who work with such models will often cite the phrase: "All models are wrong, but some are useful".
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com