Rising early career female academics and second-to-last authorship

Anyone wanna talk gender now?

Are female early career academics getting less credit for work done on behalf of (usually male) faculty who get unearned senior authorships?

My posting of a link to a PLOS One article on gender differences in academic productivity at the wonderful Reviewer 2 Must Be Stopped Facebook page drew some interesting comments. I encourage more commenting at the Facebook pages and at this blog as well.

vicious cycle journal.pone.0183301.g007

My post

Always good when data enter into discussions of whether there are gender differences in productivity and impact and, if so, why? Here are some big data….

I have noticed in the Netherlands a tendency for early career women to be next-to-last author with senior (usually male) faculty last. Knowing the circumstances of this authorship order, I think this is due to rising women taking over responsibility for more day to day supervision of PhD students, but the head of the lab keeping last authorship. Some in the NL accord more prestige or credit to next to last author, but it does necessarily get appreciated elsewhere. Does anyone else notice such practices in the NL or elsewhere?

A comment from a female Australian vision scientist

Yes, been there with next-to-last authorship. I had to fight for last authorship on a PhD student paper for which I did ALL the supervision work.

A comment from a female academic in engineering

I feel there is a huge flaw with assigning such importance to the last authorship position aspect, as I am aware that it is different between disciplines even within a country (in this case Sweden, which happens to be highly relevant). Similarly to what Kyle and others have brought up, in my field the fight is for the first positions and second positions (to escape the oblivion of “et al.,”) while the last position is reserved for the person who probably has most cred already but did the absolute least (this is debatable, because some regard getting money for the project as a full justification for being included as an author even if you do f*-all on the actual paper, while others don’t – at any rate, such aspects should have been defined explicitly in the assumption of who is “productive”, and I sure couldn’t see that in the Methods section). When I was up for tenure it was my first authorships that were counted.

And at the same time I am aware that the medical sciences (where my father does research) regards the last few authorship positions very highly. Even within engineering I am skeptical that we all reason the same regarding author position, since some disciplines (e.g. bioengineering/pharma) may collaborate with medical researchers who adhere to their ideal order…

So in the end, it bothers me VERY much that someone would want to “make science” out of making an incorrect blanket assumption about authorship order when it may vary across disciplines. Especially when I as a young female researcher have used the last position of a paper to send a message to a higher-up coauthor that “we all know you didn’t help at all.” That in particular really bothers me that it could be interpreted as being the most productive/meaningful scientist in the bunch. Anyone wanna talk gender now?

A PhD comic suggested by one commentator

phd comics authorship

The open access article to which I posted a link is interesting in itself and worth a look.

van den Besselaar P, Sandström U. Vicious circles of gender bias, lower positions, and lower performance: Gender differences in scholarly productivity and impact. PLOS One. 2017 Aug 25;12(8):e0183301.

An excerpt from the abstract:

“As the analysis shows, in order to have impact quantity does make a difference for male and female researchers alike—but women are vastly underrepresented in the group of most productive researchers. We discuss and test several possible explanations of this finding, using a data on personal characteristics from several Swedish universities. Gender differences in age, authorship position, and academic rank do explain quite a part of the productivity differences.”

Some key quotes from the article itself:

Several possible explanations of the gender differences in productivity have been suggested. (i) Female researchers are on average substantially younger than male researchers (see Fig 1), and the high productive researchers are to be found in the more senior (higher age) groups [5; 6]. If this would be the only factor, one would expect that the observed productivity differences would further decline (in line with the Xie & Schauman study [9]) and disappear over time. But also other structural and/or behavioral factors may underlie gender productivity differences, hampering female academic careers [7; 15] and leading to a waste of talent. (ii) Women are rather strongly overrepresented in the lower academic positions, and in positions with a temporary contract (Fig 2), positions which are generally characterized by a higher teaching load, less access to funding, less career perspectives, and less opportunities for research [16; 17; 18; 19]. Indeed, there is a positive relation between job level and productivity. This situation is less prone to gradual change, as it may be the effect of gender bias and of a sustained existence of the glass ceiling in academic institutions [15]

iii) Women may have less access to research funding, whereas winning prestigious research grants is characterized by gender biased in favor of men, and above that very influential for the grant winners’ career [15; 14]. (iv) Female researchers have a lower status within teams and collaboration networks, and get less opportunities to become an independent researcher. This is reflected in different author positions on papers. Women more often get the less prestigious positions: the last author (= team leader) is more often a male researcher, whereas female researchers more often occupy ‘in between’ author positions. This may result in a slower career of female researchers compared to the career of male researchers [8; 13]. More directly, Van den Besselaar & Sandström showed that men progress faster through the various academic ranks [22]. (v) Productivity relates to the organizational environment where a researcher works [23], and if female researchers have more problems in being hired in top environments [24], this is expected to affect productivity differences between men and women.

In fact, gender differences may be the effect of a combination of these five factors….

From the integrated results and discussion:

What about the gender differences? In Biology, Life & Medical sciences and in Science and Engineering, women in the higher productivity classes outperform the male researchers, as they have on average a higher number of CSS3 papers: the dotted curves (representing female researchers) for these fields are above the straight curves (representing male researchers). Also in Psychology & Education we see such trend, although in the highest productivity class the scores are equal. In Agriculture and Food Sciences, and in the Social Sciences, the pattern is opposite. As already said, in the Humanities and in Computer Science & Mathematics the pattern is somewhat fuzzy, but in the latter field there are no female researchers in the highest productivity class to compare with male counterparts.

From the Conclusion:

The first question we aim to answer is whether the positive relation between productivity and impact differs between male and female researchers. We showed that this is not the case, and the relation between productivity and the number of high impact papers is about the same for men and women within the distinguished productivity classes. On average, female researchers have a at least similar impact as equally productive male researchers. In fact, we found cases where the ratio between top cited papers and productivity is considerable higher for women than for men. More specifically, the disciplinary demography seems to produce this effect: the lower the share of women in a discipline, the higher their impact compared to male researchers within the same productivity class. This may refer to gendered selection and/or to gendered self-selection.

Secondly, we found that the higher productivity classes are numerically dominated by male researchers. This leads to a lower overall productivity for female researchers, which is also in our sample about 70% of male productivity. This ratio seems to be stable over time. We should however be careful with averages in Lotka distributed data, although nonparametric tests (Mann-Whitney) show that women are outperformed by male researchers is we do not take other factors into consideration.

Thirdly, we investigated whether other variables influence productivity, and therefore explain part of the gendered productivity differences. We indeed found that a variety of factors have an effect on performance, and controlling for those reduced the effect of gender on performance considerable. So, a good part of the productivity differences are due to the fact that men are older and in higher positions, and that those in higher positions are more productive. Female researchers also occupy less last author positions than men do, and this factor also has a negative effect on female productivity. That women more often are in the middle author positions than men, reflects that women have on average lower positions, and that they are less often (conceived as) leader of a team or a collaboration network. This finding reflects that male researchers show a faster career than their female counterparts.