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Measuring High-Growth High-Technology Entrepreneurship Ecosystems (view source)
Revision as of 13:50, 7 December 2020
, 13:50, 7 December 2020→2nd R&R
Note that there Reviewer 2 never returned any comments.
Summarizing reviewer 1's comment (reading between the lines):
*The writing is currently pretty good: '''it is well done''', '''the paper is polished''', '''very nicely done'''.
*It works as a whole. The reviewer didn't want anything cut: '''It is a collection of case studies and definitions''', and '''I don't ... major comments'''.
Reviewer 3's comments are more problematic. As is often the case, I wonder whether the reviewer actually read the paper:
*The paper advances seven new measures, not 15
*Policy cartels are introduced in section 4.1 (out of 5)
*I never use the entire battery of measures -- different measures are applicable in different contexts
*A key point of the paper is to stop organizations from self-selecting into measures that they do well on
*All bar two sentences of the 'substantive material' in the review (i.e., from "First..." to the end) don't mention anything to do with the paper
At this point in my career, I'm unique placed to give the response that every academic really wants to give to the 'self-aggrandizing idiot' that somehow always ends up controlling the fate of our hard work, namely:
:"Dear Reviewer. After carefully considering your comments, I would like the offer the following response: I find your suggestions for my beautiful paper to puerile/irrelevant/narcissistic/useless/stupid/all-of-the-above (delete as appropriate) and I'm going to ignore them and, by extension, you. Up yours."
However, it does seem that some of reviewer 3's comments would lead to improvements in the paper. These are:
#Being clearer that standardized measures aren't a panacea
#A better discussion of gaming and incentives
#Better framing in the front end of why these measures make sense (likely using the points from RFP for the special issue)
I would need to address Reviewer 3's comments point-by-point, so here they are:
#Consider possible downsides of each individual metric
#Consider possible downsides in using the entire battery of measures
#Test alternatives to this measurement approach
#Discuss when "standardized measurement" improves outcomes, when it does, and perhaps how.
#Discuss systematic bias due to gaming metrics incentivized by rewards attached to the measurement (old and new). Specifically, note that this behavioral change might have nothing to do with the underlying phenomenon of interest. (Think "Rewarding A While Hoping For B", etc., multitask, etc.)
#Justify the choices in the reduction of the measurement space Measurement is often reductive: What is left out? Is it important? Discuss the difference between the conceptual phenomenon and how it is operationalized.
#Test the effects of using a framework on various outcomes.
====Reviewer 1's Comments====
