Effects of Academic Gift Culture Surrounding Data on Diversity, a Question

Has anyone considered the gift culture of data sharing between academics in terms of it’s effect upon developing a diverse community?

Over break I was working on a literature review. There were several instances where my eyes were crossing from having opened and waded through yet another PDF. The constant supply of tea and having natural  light in my home office helped. But then in conversation with coworkers yesterday, I realized it had sparked the above question.

It’s fairly well known that there are a variety of challenges for women and minorities in academia. A study published in Nature last fall showed that faculty were more likely to respond to requests for mentoring from students who seemed, in email, to be white and male.  Other studies have looked and found disparities with hiring, promotion, salary (both salary dollars and start up funds) offers, mentoring, etc. A new study this morning looks at the web response to those studies, which turned out to be not very surprising.  In libraries, we see a highly disproportionate number of men in management positions, particularly considering that the vast majority of librarians are female, and I know I’m not qualified to address the other diversity challenges in my profession, though I’m very aware of them.

And then from my lit review:

Borgman, Christine L. “The conundrum of sharing research data.” Journal of the American Society for Information Science and Technology 63.6 (2012): 1059-1078.

Borgman gives us a comprehensive look at the various arguments for and the effort that is behind sharing research data, but then turns to the most important motivations, one of which is “To Enable Others to Ask New Questions of Extant Data.” Borgman doesn’t specifically mention a diversity aspect in this section, but focuses on the general public–often not seen as an audience for data. Still, it sparks the question of who are those others.

Wallis, Jillian C., Elizabeth Rolando, and Christine L. Borgman. “If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology.” PloS one 8.7 (2013): e67332.

Borgman’s article above gives the justifications of why, but then this article by Wallis, Rolando and Borgman asks the question of will anyone reuse the data. Examining a specific group of researchers, even with some required deposit of data, found willingness to share of “some” data, with many of the usual concerns about not losing their own rights to publication, not getting cited, etc–and actual data sharing to be pretty limited. Interestingly, most said they had been contacted and asked to share their data and had done so, though a quote from one researcher suggests that he would be hesitant if it was perceived that he would then have to answer a lot of further questions. A significant statement from the conclusions:
“Investigators share data with colleagues they know and trust, and when asked to do so. This finding reaffirms the gift culture of scholarship.”  (p. 14)
Kriesberg, Adam; Frank, Rebecca D.; Faniel, Ixchel M.; Yakel, Elizabeth (2013). “The role of data reuse in the apprenticeship process.” Proceedings of the American Society for Information Science and Technology 50(1): 1-10. <http://hdl.handle.net/2027.42/106839>
Finally, this Kriesberg article looked at zoology, social scientists and archaeologists and resuse of data. This article was particularly interesting to me because it wasn’t medicine or chemistry.  I forget sometimes how big SCIENCE can be. For these fields, data sharing and reuse norms are emerging or changing (as with most fields).  The authors were primarily focused on the relationship of mentors guiding graduate students through the process of accessing data (either their own or from a repository) and how to reuse it.  Kriesberg, et al talk about trust building between mentors and students and how reusing data can lead to a legitizmation of the new researcher.
So, we have cultures of data reuse to get new researchers started, gift cultures of academics who already know each other, and a lot of researchers wondering about if they should share their research, but this all feels still very much within a known Ivory Tower network.  What happens if you don’t have that particularly strong mentor, does the gift culture change if you’re perceived as being “one who will ask more questions” –and are those perceptions tied to perceived race/gender of the person making the request?

How would you study this?

That’s actually probably a bigger question I have.  Asking my coworkers, we talked about citation analysis–though I would argue that only shows where data sharing has been successful, not where the potential gift culture wasn’t.  One could, perhaps, interview researchers or set up some kind of thing like the Nature paper–> sending a request for data using names that appeared to be of a specific gender or ethnicity and evaluating based upon response. My guess is there would need to be some serious network/systems analysis and probably interviews or focus groups on both sides: data sharers to parse out how they might respond to a request and from those requesting to see if they perceive that they wouldn’t get data or hadn’t gotten data due to a bias.

I think this could be one of the arguments for making your data public. It won’t hold water with a lot of people, but it’s something to consider–> who might need access to your data or have a brilliant idea for reusing your data that might never gain access to it because a) they have to ask or find someone who knows you to ask; b) you may not respond based on personal prejudice against [fill in prejudice here].

If anyone has already sorted this out and I haven’t found the article yet, please put it in the comments.  Also, bravo to the authors of these articles that I could easily find OA options to share! Thank you.

One Comment

  1. Comment by Eric Hellman:

    Perhaps I can help here. I worked as a scientist for about 15 years. Coming from elite institutions with well-known mentors I never encountered resistance to my information-sharing requests; in fact sometimes almost the opposite. But as I became known in my field I would get many requests for information and material sharing.

    The big factor in deciding whether to assist with a particular request was how much effort I would need to extend. Some things, like sending a preprint, took no work, so the barrier was low. If effort was involved, the main consideration was “Is this person an idiot?” Because I would get requests which were transparently from people who either were ill-informed or crazy (And I don’t mean mad-scientist crazy, I mean sad-crazy.) The idiot test was important because working with someone smart was rarely costly in terms of time, working with an idiot would be costly in terms of invested time.

    So I’d imagine that data-sharing behavior is mostly reflective of competency assessment, and the effect of race/gender/etc on data-sharing comes entirely from its effect on competency assessment. I would imagine that each of these two links (sharing-competency and competency-diversity) might be easier to study/measure than the sharing-diversity link.

    Hope this helps!