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2013 most read posts.

These were the most read accessed posts at Seeds Aside in 2013:

Of course, these are mostly older posts. I should go back to older days writing style. I should…

The worste recorded was this one:

Title not so say! :)

Request were mostly single words, probably something that changed in search behaviour in recent years (too bad, it was funnier when people typed questions directly and resulting direction was mismatching…):

- roucou, mosses plants, drip tip leaves, achiote, contrepèterie en anglais, miltomate, male orchid, contrepetrie in english, meiosis, meiose…

 

 

 

A Carnival of Rocks and Plants

Go read!

Go read it there.

Gogonuts palm edition, perhaps oddy a psalm oddly…

#MyGenderGap filters out

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:

How to calculate #MyGenderGap for publishing scientists

#MyGenderGap

#MyGenderGap – my history of inequality in numbers

My CV is a Sausage Fest

#MyGenderGap

The stream is mostly in tweets, you can still reach them to get an idea… even if untweeting. Or even better, just here.

I’ve crossed the following post at Denim & TweedThe 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:

Skewed gender in published research.

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…

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