“You might have heard that scientists use what’s called the scientific method, a virtuous cycle of generating and testing hypotheses which supposedly separates the good ideas from the bad ones. But that’s only part of the story because it doesn’t tell you where the hypotheses come from to begin with.
Science doesn’t operate with randomly generated hypotheses for the same reason natural selection doesn’t work with randomly generated genetic codes: it would be highly inefficient and any attempt to optimize the outcome would be doomed to fail. What we do instead is heavily filtering hypotheses, and then we consider only those which are small mutations of ideas that have previously worked. Scientists like to be surprised, but not too much.
Indeed, if you look at the scientific enterprise today, almost all of its institutionalized procedures are methods not for testing hypotheses, but for filtering hypotheses: Degrees, peer reviews, scientific guidelines, reproduction studies, measures for statistical significance, and community quality standards. Even the use of personal recommendations works to that end. In theoretical physics in particular the prevailing quality standard is that theories need to be formulated in mathematical terms. All these are requirements which have evolved over the last two centuries – and they have proved to work very well. It’s only smart to use them.
But the business of hypotheses filtering is a tricky one and it doesn’t proceed by written rules. It is a method that has developed through social demarcation, and as such it has its pitfalls. Humans are prone to social biases and every once in a while an idea get dismissed not because it’s bad, but because it lacks community support. And there is no telling how often this happens because these are the stories we never get to hear.
“What it’s saying is that people who go through a certain training and who read these articles and who write these articles learn to write in a very specific language. This language, this mode of writing and the frequency with which they use terms and in conjunctions and all of the rest is very characteristic to people who have a certain training. The people from outside that community are just not emulating that. They don’t come from the same training and so this thing shows up in ways you wouldn’t necessarily guess. They’re combining two willy-nilly subjects from different fields and so that gets spit out.”
In theory development we always have a tension between simplicity (fewer assumptions) and precision (better fit) because more parameters normally allow for better fits. Hence we use statistical measures to find out in which case a better fit justifies a more complicated model.