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Daniel Lemire and colleagues are aiming to find a better algorithm to measure importance of research articles by incorporating the context in which the citation is made (for example, distinguishing between “courtesy citations” inserted to placate referees and real pointers to important work). They need some data and it looks like a low burden for each researcher to provide it. Check out http://lemire.me/blog/archives/2012/03/20/from-counting-citations-to-measuring-usage-help-needed/ for more.
I think we have passed the point of no return with bibliometrics in evaluating researchers and articles. They will be used, so it is to our benefit to ensure that less bad ones are used.
A related topic: can we and should we have some recommendations for how to cite properly? If citation indices are going to be more highly used for evaluation of research(ers), as I believe they will in the near future, surely it makes sense to try to adopt reasonably standard practices. I am sure this has been discussed on this forum but can’t find it, so am adding it here. MathOverflow has some discussion on related topics, but not this one as far as I can tell.
Ideas:
I wouldn’t endorse the idea that we should change our citation behavior for the sake of bibliometrics. Citations serve a really important purpose, and it’s not worth compromising that to help with their side application in evaluation.
limit the number of citations allowed in any one paper
Of these ideas, this one seems the most problematic. In extreme cases, I can imagine saying someone was citing too many papers. (Imagine a brief note with a gratuitous 1000-item bibliography of all work ever done in this area.) However, within reason I believe authors should be allowed to cite as many papers as they consider appropriate.
explain to people that courtesy citations… should be avoided as much as possible except in survey articles
explain to beginners that citations should be to the first, the best and the most recent work on the topic
I’d argue that many papers should be a little more like survey articles, rather than less. Not to the point where it becomes a distraction from the main purpose of the paper, but a bit more background for beginners is usually helpful, even sometimes for experts. I don’t recall ever reading a paper where I wished the authors had cited fewer sources, but I have read papers I thought should have cited more.
I worry that citation measures will be increasingly used, and we can’t stop it. So I would like them to have a more standardized meaning. They do serve an important purpose, but I am not sure that there is agreement on what that purpose is.
Here is another semi-random thought. Maybe we should have two types of citations, and they should be distinguished. The first type is everything that is essential for the paper, in the sense that without the cited work, the present work is incomplete. The second type is for all other citations (mostly courtesy). Papers could have a separate section for all the second type citations, and the first type ones are cited when needed in the body of the work. These would have to be enforced by a journal, for example. I can see that there would be problems implementing this, because it might be tempting for authors to include all arguments so as to shorten the first list, or include almost none by citing far too many other works (although the latter presumably will make the present paper seem rather weak so I doubt authors would do it). It might also be tempting for some not to give credit to earlier work. I suppose that incentive is already there in some sense (at least, it is easy to be lazy in looking for that earlier work) and it is an issue that should be addressed by refereeing, but I’m not sure about exactly how.
If citation measures are not used for evaluating quality/impact of research, then what? I am very suspicious of judgments on the quality of mathematical works made by small in-groups of “experts”. Widespread (“crowd-sourced”) ratings might be good, but the problem many people foresee is that almost all works will receive no ratings.
Of course if we are only about the quality of research produced overall, most of these considerations are less of a concern (for example, there are big incentives now to collaborate on papers, since the credit does not seem to be divided between the authors - this can be a problem if we evaluate individuals, but isn’t a problem for the overall research enterprise). But I very much doubt we will achieve this kind of world very soon. In fact it seems to me that trends are going the other way.
I agree with most of Alexander’s comments - we should only really be making quite crude distinctions, perhaps at most 4 equivalence classes of researcher ability. I do advocate randomness in decision-making in some situations where it still seems to be socially unacceptable. In this case math researchers usually also teach and do administration, so evaluation is not just based on research. And I am past worrying about getting a job (unless something very bad happens where I am now). I am more concerned about concentration of resources such as funds for PhD students and postdocs, which, if crude quantity-based measures of research output are used (and unfortunately they are rather more widely than we would like) just lead to even more production by those with the extra resources, but not necessarily an advance in science or a good use of human capital. (That is close to my record length for an English sentence).
Unsurprisingly, other people have encountered the same issues regarding standards for citations. Here’s a short introduction by Martin Fenner to CiTOs which some reference managers already support.
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