I think a better metric for the “academic productivity of org. X” would be “academic papers mainly affiliated with org. X (this can be operationalised e.g. as the main author being mainly affiliated with org. X)”/∑i”number of authors of the academic paper i mainly affiliated with org. X”:
I think productivity usually refers to “output”/”input”. So, if you like, you can divide your metric by “number of authors mainly affiliated with org. X”.
It seems fairer if only papers mainly affiliated with org. X contribute to the productivity of org. X. For example, Alexey is affiliated with ALLFED, but his 6 papers have not much to do with ALLFED’s mission.
This metric avoids double-counting papers.
(Ideally, the denominator would be ∑i“number of hours invested in the academic paper i mainly affiliated with org. X”, but this is not available!)
Interesting post, Florian!
I think a better metric for the “academic productivity of org. X” would be “academic papers mainly affiliated with org. X (this can be operationalised e.g. as the main author being mainly affiliated with org. X)”/∑i”number of authors of the academic paper i mainly affiliated with org. X”:
I think productivity usually refers to “output”/”input”. So, if you like, you can divide your metric by “number of authors mainly affiliated with org. X”.
It seems fairer if only papers mainly affiliated with org. X contribute to the productivity of org. X. For example, Alexey is affiliated with ALLFED, but his 6 papers have not much to do with ALLFED’s mission.
This metric avoids double-counting papers.
(Ideally, the denominator would be ∑i“number of hours invested in the academic paper i mainly affiliated with org. X”, but this is not available!)
Yeah good point. I’ll probably do it differently if I revisit this next year.