[not2b]

There's no evidence from this article that the idea space is decreasing. Vocabulary is becoming somewhat more similar: the measurement is on individual words. Suppose an institution decides that the faculty is using overly obscure language (or a grant-making agency decides this) and asks that grant submitters reduce the amount of jargon, include more background, etc. Wouldn't this measurement then show a significant drop in the distance measure? Note that I am not saying that this is what is happening (I seriously doubt it, in fact), but I think too much is being concluded based on this measurement.

[_xnmw]

Words represent ideas. Fewer words is good evidence that there are fewer ideas.

Sometimes multiple words represent the same idea, so in that case homogenization is "good". It is also possible that multiple ideas are represented by the same word, but that is "bad" in an academic context because it leads to ambiguity. Therefore fewer unique words IS actually good evidence that the idea space is decreasing, unless you are saying academic literature is becoming more and more ambiguous.

[avs733]

Words don’t represent JUST represent ideas.

Words transmit ideas. The difference is notable I’m this data set in particular. I posted a longer version elsewhere in the thread but to summarize.

During this time period the nsf became more strict about explicitly addressing their review criteria. Faculty became trained to use the languag explicitly and connect their ideas to the language of the review criteria. I’m effect, you started to get an ‘api’ where, irregardless of what the idea in the grant is, it’s is clearly and explicitly connected to key nsf terminology. That is a de novo narrowing of the language space no matter the underlying ideas. It’s purpose is definitively about improving communication, not narrowing ideas.

From what I can tell the paper didn’t filter anything in the data. Had they filtered “broader impacts” and “intellectual merit” I would be hard money they would get different results.