Go read it there.
Yes, I know I was five days away from the initial buzz, but considering how slow stream Seeds Aside is, that’s not too bad. (This is perhaps the first time in its history that SA is taking a ride at all :)
A few blogs have analysed the extant of the gap:
I’ve crossed the following post at Denim & Tweed –The science gender gap gets personal with #MyGenderGap, from which I’ve decided to steal the title. I’ve no twitter account yet (is that a fail? More and more academics are using it, but apparently biologists do poorly so this is just because!), so the only way to deal with the issue is to go blog about it.
The issue is about bias in gender in Academia. There’s been occasionnal mention to this issue here at SA (e.g. Gender & publishing), though just passing by (I’m not in a position to create new views, arguments or meaningful analyses on that matter, and there are plenty places where such things are produced or discussed so I usually get away with providing links).
It is all about a recent comment in Nature, which I’ll quote:
Thanks to Anne Jefferson on Twitter, I see that Alex Bond has called our collective attention to Nature’s great feature on gender equity in the sciences by making the whole thing as personal as possible: asking people to total up their collaborators and see what female-to-male ratio they find(…)
I’ll go more personnal below, but before, just have a look at their interesting map (it is just below if you don’t happen to have access to the journal): some countries just perform much better in term of women inclusiveness in science publication world:
I don’t have field work pictures as Jeremy does, but it’s also true that most of my field times are rather lone or with reduced crews. Much of my previous work doesn’t strictly rely on field work but includes various lab steps, so I’m still able to crunch magic numbers about female to male ratios from my different work experiences past.
When I first counted collaborators (just including people with whom I published), raw numbers are 14 women and 7 men (that would be 8 if I count myself). So basically the sex ratio is 2.00 for my collaborators (1.75 if I collaborate with myself :) that should count since I’ve already published a single author paper).
That’s rather huge, compared to the USA average of 0.43 Jeremy noted (EDIT: 0.50 in France, but my work experiences are both in Fr & USA). But that’s because I’ve mainly worked in female biased labs throughout my early career. (it’d be interesting to keep track of the numbers as I currently work at a place where potential authorship should have a reversed trend –I should care about it clearly…)
At first, I investigated the numbers with counts on each paper, which yields a slightly different picture, since people are counted several times. My first ratio was 1.37 and I wondered why it differed from co-author ratio (which was 2.00). Then I realised I counted myself on papers but not in the collaborator sample. So when I drop myself from the papers, the ratio is 3.25 (that’s because I published regularly with the same female colleagues).
Whatever the calculation, I’m always in an atypical situation.
Of course I’m not discovering this: I already knew my work experience differs from most scientists because the basic or average place is biased toward strong maleness while my own path only crossed the reversed situation. Though I have to say that I happened to realise it only because people discuss the issue of gender bias (thanks internets! It’s never been discussed at workplaces). It never crossed my minds how outstanding my professional situation was before I read about this gender issue in Academia. But there’s something weird about this. I don’t know whether it’s telling something or pure luck is involved: if the common situation is a male dominated Lab or Team, why did I never experience it (over 6 different work settings)? Is there anything that prevented me to work at the average Lab place? If so, we clearly all need some more awareness that there’s an issue, and it’s not getting away fast enough…
You may find interesting consequences of megajournal open access journals (that’s impressive in term of numbers):
And this talk shared there: Open Access MegaJournals.
Certainly there’s been a change in the science publication ecosystem (that’s obvious). Unsure as to whether some aspects are easily documented, though:
- actual replication is accepted, but is it easy to find out which studies stand as replications from earlier works?
- “minor results” may indeed have found a way in the available “results pool”, but how do you say? It was clearly an issue prior to open access, since reviewers could reject on the basis that results were not interesting (whatever that meant), but OA doesn’t delineate between results unfairly rejected on spurious motives and “minor results”. Weren’t citation fate of papers telling us about fanciness already? (and not scaling on interestingness anyway!)
Did you ever get the feeling that these two aspects were saved by OA in specific cases? I haven’t yet. Which doesn’t mean it isn’t happening (I’m only saying it doesn’t read well even between lines). Or was I already swimming and reading in the pool of “forgotten studies”?