It is not unusual to read the tirade of a senior scientist complaining that science was better back then, when papers were fewer, and ideas better (a perfect example of this genre is here). Usually, the conclusion is that we should publish less, lest producing lower-quality science.
These considerations are based on a quite precise hypothesis— that a scientist can either produce many papers, or produce fewer good ones. Detecting such a trade-off in actual data is quite difficult, though, as scientists vary dramatically in productivity, as well as field of study.

Matt and I tried a different route, and compared scientists with themselves: does a scientist produce better papers in the years when she’s most productive? For testing our method, we took the members of the National Academy of Sciences, and reconstructed their publication history. (The rationale being that their best papers must be of high quality).

We found that these scientists tend to produce their most recognized work in years when they’re most productive. However, they also tend to produce their least impactful articles during the same productive years. This is consistent with the random impact hypothesis: by publishing many papers, scientists sample their distribution of good ideas more thoroughly, leading to higher maxima and lower minima. You can read the paper here:

Matthew J. Michalska-Smith & Stefano Allesina
And, not or: Quality, quantity in scientific publishing
PLoS One, 2017