(This post is a continuation of my post of last week and gives some better grounded data.)

As already hinted at, if you are a scholar active in Europe, you will most probably depend on funding for your projects in order to survive, given that surviving out of teaching alone is infrequent and a tenure is not foreseeable. Thus, it becomes essential to know what one’s chances are.
A short comparison shows that among European countries,

  • Switzerland is the one in which more money for research is granted (total amount/number of inhabitants): 88,5 E pro inhabitant each year
  • Finnland is the next one: 61,1 E
  • UK (Research Council UK): 48,0 E
  • Neatherlands (NWO): 37,2 E
  • Germany (DFG): 33,5 E
  • Austria (FWF): 23,8 E

This is however still not enough, since a lot depends on how many funding agencies there are in each country, so that, e.g., the situation may look different in Germany if one takes into account also the Humboldt scholarships, the Max Planck foundation, etc.

Moreover, the amount of money available per inhabitant still does not say much, since it is not said how many inhabitants apply for that money. In this sense, it seems that the acceptance rate of the German DFG is much lower than expected, whereas the Swiss acceptance rate is high, as expected:

  • Swiss acceptance rate: around 50%
  • Austrian acceptance rate: 25,8%
  • German (DFG only) acceptance rate: around 17%

Still more interesting, especially for prospective peer reviewers are the following data:

  • acceptance rate in 2008 (Austria, FWF): 43,0% (2008 was the highest peak attained, before that the rate was around 41,5%)
  • acceptance rate in 2013 (Austria, FWF): 25,8%

Why this huge difference in a few years? Because the number of application has been incredibly growing (from 1,000 in 2001 to 2,386 in 2013).
This means that the lower acceptance rate is not due to the lower quality of post-2008 projects. Rather, after 2008 the FWF Jury (and I imagine that a similar situation applies to the DFG and similar fundings) just had to look for weak points in each project in order “not to go bankrupt” (precise quotation of what I heard at a recent FWF roadshow).
Given that the decision about a project is taken in Austria, Germany and Italy (I guess that the same applies to the other EU countries, but I cannot be sure) by a jury or committee on the basis of peer-reviews, much burden lies on the peer reviewers themselves.
Again, as I heard at the same roadshow:

We are forced to look for anything which looks like a critique, if we want not to go bankrupt. We know we are turning down projects we would be funding in better financial conditions.

There is nothing blamable in that, but I am convinced that peer reviewers should be informed about the weight of their decisions. Anything less than “enthusiastic approval” amounts to good news for the committee, who can turn down the project. It is fine, if you think the project not to be worthy, but I, for one, will send my further suggestions directly to the applicant and not include them in my peer review the next time I am asked to review a project.

Source: FWF

This post has been published, with minor variations, also on my personal blog.

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6 responses to “Funding your research projects: some data”

  1. Hi Elisa!
    I think the reviewer’s primary responsibility is to provide information about both pros and cons to the selection committee of the funding agency in question so that informed decisions can be made (rather than to the applicant). I’m not sure why the reviewer shouldn’t both express enthusiastic approval and provide suggestions about improvements and point out minor weaknesses. After all, I suspect that selection committees have to decide among projects which all get enthusiastic approvals from reviewers (I’ve never been involved in such a process, so I don’t know). In this case, information about minor weaknesses (perhaps conveyed as suggestions) may turn out to be crucial for a committee’s final decisions, but why is that a bad thing? At least, this seems better than picking at random from the final pool of projects. But perhaps there are even better alternative procedures that haven’t crossed my mind.
    Cheers
    Olle

  2. Olle, thanks for the comment. The situation is hard and this makes it difficult to be fair. However:
    1) my point is that in the new language of funding committees, terms such as “suggestions” now mean “weak points” or “reasons for turning down the project”. A referee is very welcome to fill in adequate reasons, she just needs to know what she is doing.
    2) I do not agree with the idea that the reviewer’s primary responsibility is towards the funding agency and not towards the applicant. Personally, I am convinced that whenever I turn down someone, she has to learn something through the process and to at least gain the opportunity to improve. In this sense, confidential remarks which are only read by the committee are unfair, because they deprive the applicant of the opportunity to grow and learn.

  3. Thanks for the reply Elisa. I didn’t mean to disagree with 2, and perhaps you are right about 1. I just meant that that a reviewer should not tailor her/his review to whether or not s/he wants the project to be funded. If s/he really likes a project and thinks it is very worthy of funding, s/he has no responsibility toward the applicant to try to ensure that the project gets funded. The reviewer knows nothing (or not much anyway) about the other projects competing for funding, so it seems to me that s/he should try her/his best to convey the relevant pros and cons to whoever makes the decisions. I also think it is important that the applicant gets information about why the project isn’t receiving funding so that the applicant can improve the application (so I don’t disagree with 2). It is of course also important that the decisions are as fair as unbiased as possible. I’m sure there is of luck involved, and well as a lot biases. And so, there is a lack of fairness too.

  4. A lot depends on the process used to evaluate the applications. In the Netherlands for the VENI postdocs (success rate between 15-20% over the past few years AFAIK) the candidate is invited to respond to the referee reports. I managed to turn around one negative report (out of three) by succesfully addressing the issues raised by the referee (see: http://blog.ierna.name/2013/01/22/veni-grants/ and http://blog.ierna.name/2012/05/28/from-the-peer-review-to-the-interview/ ). In this situation, the committee gets to evaluate the proposal on the basis of a back-and-forth between the candidate and referees, which mitigates the issues you raise. Instead, to make a rough cut, almost half of the applications are eliminated based on a pre-selection, before the proposal goes to the peer-review phase. Just by looking at CV and a layman’s summary the committee chooses which proposals to forward to the referees, but only if there are more than four times as many applications as can be funded within budget.

  5. Hi Olle, and sorry for the late answer. Now, the issue is really thorny, insofar as, as you rightly say, the peer reviewer has no idea about the other competing projects and little idea about projects presented all over the world, but nonetheless s/he in invited to say whether the project is among the top 5% (so in the Austrian FWF) or top 15%–20% (as in Carlo’s example) among similar projects in the world.
    The only point we keep on disagreeing about is whether the peer reviewer is responsible of the final choice or not. I see that in an ideal world explaining pros and cons of a project would be the right thing to do. However, in our biased world, this basically means that the project one is reviewinig will be immediately turned down (see quotation above) or has far less chances (see Carlo’s experience as depicted in his posts). I, for one, would not want this to happen if I believe in a certain project and has only minor suggestions about it.

  6. Carlo, thanks a lot for the comment and for the interesting posts about your experience with the NWO. Whenever you have time, it would be interesting to have some more raw data (% of accepted projects among the ones who got less than A in at least one peer-review, whether the number of accepted project is decreasing, number of projects of incoming scholars accepted…).

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