PhD career interests patterns #DiversityJC recap

And here we go with the last #DiversityJC of the year. I’m so happy that we are keeping it up and that our journal club is getting bigger and stronger! This week our discussion was about how the career interests of biomedical science PhDs patterns change according to race/ethnicity and gender. You can see the full article here.  Also, you can read the complete storify kindly made by @MinorityPostdoc.

@labroides started venting about how the article casts leaving academia as problematic. (What IMO is a very good issue and I’m planning to write a blogpost about this soon). “But putting that to the side, the real question is why do we see this differential filtering?” @aiquintero mentioned it isn’t because URM&W aren’t successful, motivated, well-mentored. @IHStreet suggested that in tough economic times, people stick to status quo/less openness. Although the decline in $ for research is general, this may be harder among women and even harder for URMW.

However, @biochembelle mentioned that the article shows women exhibit lower interest in research faculty path even at start of PhD. So why this happens? Some sort of impostor syndrome?@aiquintero stated that # of publications, mentorship, etc was controlled for (in the article). If professional success ~ fit, then something else is missing! @CEK_1of9 replied that it might be the classic problem of no role models that “look like me”, which starts in graduate school. @IHStreet added that there are more visible women in STEM than ever. But may still be early days yet to really drive change. But how can women find a niche if they don’t apply? (Studies show bid drop in number that apply for TT positions).

Along this line @drugmonkeyblog continued saying that Recruitment and retention can be salary, research support, techs, postdocs and even jr faculty lines. Yet you should hear the mewling and whining should anyone suggest paying a huge bonus over expected to recruit a PoC. So *of course* Universities continue to fail to *look* diverse and therefore create impression it is impossible as a career.

@SFBakshi wondered if conference participation/networking in grad school plays a role in choice to pursue academia. The article states that perceived sense of “belonging” – either intellectually or socially – was not associated with interests. Although authors note as study limitations that respondents might try to give “socially acceptable” answers. But this goes together with the line of thought that is not straight impostor syndrome.

@biochembelle replied that this study provides some measures. It doesn’t provide “why” (part of future work). So, how do you encourage the interested without dismissing those who aren’t? There are some programs trying to address this, eg this one from Northwestern

@aiquintero suggested that academia is repellant because perceived as hostile to family/work-life balance. This was questioned by @DoctorZen: More than professions like medicine, law? Not known as relaxed environment. Not really, but those professions tend to pay better & have diversity of practices. So the problem is in academia, or professions more generally? Probably both!

I believe I will end up with this as food for thoughts for next #DiversityJC. We will resume it next year, January 9th, 11EST. Please let me know if you want to be included in the email list or if there’s a suggestion to change the day/time of our journal club next year. Happy holidays and see you in 2015!

4th #DiversityJC recap – guest post by @DrEmilySKlein

My dear Diversity Journal Club,

 First and foremost, my sincerest apologies for not having this blog to you sooner. I blame traveling and jetlag!

 Emily

Computing power is increasing rapidly, and with it the questions we can ask in a range of fields. Tasks that seemed beyond reach, and then once took hours or even days, are now happening immediately and with enhanced flexibility. For my own work, I’ve coded in rudimentary R, then Matlab, and have used command line and remote servers to access powerful model code and run reams of data. Currently, I’m trying to learn Python and, more recently and with more difficulty, Julia (this language is not intuitive for me).

Despite the increasing importance of knowing how to code, it seems doing so runs along some familiar boundaries. A recent NPR story connected a decline in women coding with advertising of computers focused on boys. Girls no longer felt computers were “for them” and ended up avoiding coding, while boys taught themselves. The difference, of course, manifests itself later on – when young women also fail to enroll in coding classes, despite the increasing importance of coding in a multitude of fields.

Last week’s Diversity Journal Club focused on this NPR story, and the potential barriers to learning to code. Immediately, our topic seemed to strike a nerve.

People want to talk about coding.

Coding is a big deal these days. It’s increasing rapidly (exponentially even) in importance and application. In my line of work, it’s no longer recommended but required. You’re asked not if you code, but what languages you use.  But learning to code is challenging – as was pointed out, it is literally like learning a new language.

The NPR story, and our discussion, highlighted how that challenge also falls out along gender, and other diversity, lines. We quickly got into how much support is critical, starts very early, and as InBabyAttachMode (@BabyAttachMode) put it: the “implicit and explicit statements about computers/coding being for boys is key”.

Indeed, although Evil Lucian (@FoolsExperiment) noted how much having a parent teach you general curiosity and the same skills along with your male siblings can be critical, this can be undermined when even those parents have still internalized our societal gender binary – and are “surprise to find [their daughter] there handing him tools instead of playing with Barbies.”

Implicit, and explicit, bias and stereotypes have concurrent outward consequences, like developing and seeking out new skills, or internal ones, like seeing yourself as capable or incapable of doing something and having confidence in your abilities.

We start to internalize things that can seem rather insignificant. If society, the media, advertising, other people (or their messages) tell us (even indirectly) that something isn’t for us, we tend to start believing it’s because we can’t do this thing.

In addition, those that are privileged with supporting messages and access, those who already have the skills and could teach you – don’t get the issue, or the barriers.

Moreover, they likely also got the message and also believe we can’t do this thing.

These barriers are pervasive, and translate widely. Any difficulties you may have in learning are tagged as personal limitations – not a place to offer support. The culture itself becomes another barrier, and extends far beyond “computers are for boys!” advertising.

In addition, the lack of diversity in anything can have more drastic consequences, and changing that inofitself can be crazy difficult. People hate giving up their privilege. To the coding and gaming topic, this has translated to men feeling ostracized (??) by women entering gaming spaces, despite the fact that it’s actually life-threatening (hashtag-Gamergate) for women.

There’s also the myth that you have to learn it when you’re younger, so you might as well give up if you don’t already know it.

If you didn’t have a computer, or were told you shouldn’t want one, and now you need to know how to code, but it’s challenging and people are telling you “well, shoulda learned that already…

To sum up: While the NPR story highlights the idea that girls stopped coding because advertising for computers targeted boys, because “boys like computer games and math, and girls like dolls”, the lack of girls in coding translates widely, and creates real barriers to women in coding, despite its increasing importance.

These biases and barriers are likely not just gendered.

It’s also about resources and access. If you couldn’t afford a computer, it didn’t matter your gender. We all know that socioeconomic class is often along racial lines as well. This is likely not just when you’re younger, but as you advance in your career – do you have access to computers and coding education? In addition, do you have the time to learn?

This made me wonder how these messages also run along other lines of diversity. To me, it seems that coding is really for white, privileged boys.

We did, however, wonder how much this was clouded by where we lived. As biochem belle (@biochembelle) pointed out, women were well-represented in Malaysia, and The New PI (@TheNewPI) noted computer science is popular with girls in the Middle East. We should be careful to avoid generalizing based on our own experiences – and what were they doing right? What can we learn from that?

Finally, Doctor PMS (@Doctor_PMS) played @labroides and asked what we do about this?

We need education – starting at a young age, but also through higher ed. We need greater access to resources across the board.

We also need to “demistify” coding and math as for boys (@Doctor_PMS), and we need to show that many people code (@mccullermi), and that it can be learned at any stage in your career.

Getting us over the initial challenge of seeing ourselves as being able to code is also demonstrating, as NotThatKindaDr.Kline (@MichelleAKline) points out, that it’s not a “magical talent/gift”. Doing so may be very simple, too:

In addition, we should be making clear that coding can be critical for research, and is likely increasing in its importance. It’s not just about learning to code, it’s about why you should – about learning that it’s a skill, a part of research.

We also need to stop with the “coding wars”. As Cheng H. Lee (@chenghlee) pointed out, it’s a field that can be “abusive towards ‘outsiders’”, and drawing lines around which languages are “right” or “better” also makes navigating the coding world that much more intimidating. @chenghlee went on to point out how focusing on a preferred language can be used to deride and exclude others, and Laura Williams (@MicroWaveSci) noted it was “gate-keeping” that also drove newbies away.

I also think we just need to talk about this. We need to air this out. We need to a space to talk about our experiences, to understand we’re not alone in feeling this. That biases and their consequences are pervasive and systemic – and that they last.

Finally, there are little things we can each do to help learn coding ourselves.

Although Megan McCuller (@mccullermi) noted that we need hands-on experience too – and this can be a challenge. Laura Williams (@MicroWavesSci) followed up that “small doses of exposure” may help – but I have to agree that getting experience can be tough. For me, I often google the language I’m learning and “online tutorials” to get free exercises I can run myself. Of course, the Lynda classes I have access to via Princeton are also great – but have a cost! There are other free (http://www.codecademy.com/) pay-for (https://www.codeschool.com/) online schools too.

And, of course, one thing not to do:

GIRLS DON’T JUST LIKE PINK AND DOLLS, ALREADY.

Instead, maybe we start real conversations and real communities about this.

I think this is a fantastic idea – who’s with me?

In my personal opinion, the conversation around coding really crystalized much of the barriers across STEM fields. First, the messages we received from an early age and throughout our careers on what we can and cannot based solely on physical attributes and generalizations. These barriers are not necessarily obvious, but can be deeply internalized – both for those marginalized and those with access. Second, it’s not just the message, but the resources we have available. Not everyone can afford a computer at home to learn on, or goes to a school that has them widely available. These resource barriers can extend beyond high school graduation. For instance, in addition to programs for personal computer purchases, my current home, Princeton University, provides free access to Lydia courses. These offer a huge range of online tutorials for almost all the programming languages (I haven’t seen Julia there yet… I looked), from beginner to advanced. These offer a personalize way to learn programming, outside a classroom where it can be intimidating. I have no idea how much a Lydia subscription costs, but it may be an example of a resource not all institutions have.  Third, our conversation also made clear, once again, the importance of community, of having people to commiserate with certainly, but also people you can identify with. People who make you feel normal, that the difficulties you have are normal – and not an actual personal failing.

Finally, some links and resources shared:

A Teenager Gets Grilled By Her Dad About Why She’s Not That Into Coding: https://medium.com/matter/you-should-learn-to-code-is-the-new-you-should-go-to-law-school-talk-dads-love-to-have-b03bd22b3c99

Beginning Perl for Bioinformatics: http://cbb.sjtu.edu.cn/course/database/beginning.pdf

The Intersection of Gender, race, and Cultural Boundaris, or Why is Computer Science in Malaysia Dominated by Women?: http://sss.sagepub.com/content/39/6/885.short

The reddit conversation over “When Women Stopped Coding”: http://www.reddit.com/r/TwoXChromosomes/comments/2jmq9u/when_women_stopped_coding/

Gamasutra: http://www.gamasutra.com/blogs/LaralynMcWilliams/20141030/229072/Shes_Not_Playing_It_Wrong.php

Thank you to everyone who participated (apologies and let me know if I missed anyone or got anything typed in wrong)! Give these fine folks a follow…

Laura Williams (@MicroWaveSci)

Megan McCuller (@mccullermi)

Rebecca Pollet (@rmpollet)

InBabyAttachMode (@BabyAttachMode)

biochem belle (@biochembelle)

Alycia Mosley Austin (@AlyciaPhD)

Josue Ortega Caro (@josueortc)

Cheng H Lee (@chenghlee)

Elita Baldridge (@elitabaldridge)

Urbie Delgado (@urbie)

The New PI (@TheNewPI)

Caitlin Rivers (@cmyeaton)

Eric Lofgren (@GermsAndNumbers)

Bree Sxostek Barker (@MicroBreePhD)

NotThatKindaDr.Kline (@MichelleAKline)

Wandering Scientist (@wandsci)

Colin Quirke (@ColinQuirke)

Let It Go, 134 Times (@colinized)

Evil Lucian @FoolsExperiment

‘Til next week!

XX

Emily (@DrEmilySKlein)

Doctor_PMS (@Doctor_PMS)

Jonathan Goya (@jkgoya – who could not join us last week).

3rd #DiversityJC recap, guest post by @jkgoya

Our third #DiversityJC article was this letter presenting and analyzing the changes in women and minority involvement in the Ecological Society of America, at both the membership and leadership levels. As a letter from members of the Society, to the Society, critiquing the Society, it represents an important type of critical feedback, and it gives us a chance to see the Society’s response to the letter (as well as the community response).

The letter suggested that the absence of women and underrepresented minorities in the Society leadership could be attributed to either a time lag as we wait for the recent changes in membership proportions to propagate to leadership, or that selection committees preferentially exclude women and underrepresented minorities from consideration, whether intentionally or otherwise.

I think we agreed here, that just giving it time would not lead to balancing out the proportions.

Another point that was discussed was that it’s often potentially damaging to one’s career to speak out about these kinds of issues (diversity, harassment, injustice generally). I’ll leave off embedding those tweets as it seems wrong to publicly blog an embedded tweet in which someone expresses concern about speaking out.

We also discussed what happens outside of academia. Is it better or worse? What role does academia play in the larger culture?

 

Finally, many links were shared to try to answer some of these questions:

The importance of open access to research for supporting diversity:

http://blogs.biomedcentral.com/bmcseriesblog/2012/12/06/guest-blog-why-i-publish-open-access/

An example of the scale of hostility that can exist outside academia:

http://www.nj.com/business/index.ssf/2013/05/post_269.html

Reports from various STEM-related organizations on career trajectories:

http://www.nsf.gov/statistics/wmpd/2013/start.cfm?CFID=16466301&CFTOKEN=55531281&jsessionid=f030f7015d517b2f872e303224a2f61e45f3

http://www.asbmb.org/asbmbtoday/asbmbtoday_article.aspx?id=15855&page_id=2

http://www.biochemistry.org/Portals/0/SciencePolicy/Docs/Chemistry%20Report%20For%20Web.pdf

http://www.theguardian.com/higher-education-network/blog/2012/may/24/why-women-leave-academia

http://diversegreen.org/report/

#DiversityJC recap, guest post by @DrEmilySKlein

“According to my clock it’s 1100EST, let’s get this #DiversityJC rolling!”

 

And with that, we were off.

 

You know, it’s funny how things get started these days (especially for a twitter newbie like myself). One little tweet can ring so true, and next thing you know, you’re talking with complete strangers over the interwebs. But they don’t really feel like strangers, do they?

 

The Diversity Journal Club (#DiveristyJC) was born of conversations between Jonathan Goaya (@jkgoya), Doctor PMS (@Doctor_PMS) and myself (@DrEmilySKlein). For our first paper, we discussed the one that got it all started (learn more here, and read the article here. The premise of the paper was that women get more positive feedback on their grant proposals than men do.

 

And our thoughts?

 

First and foremost, many had concerns with the methods used. Of course, as scientists assessing study in an unfamiliar field, we tempered that with a healthy dose of “well, the methodology was new for me so…”. Regardless, we generally agreed that the methods had to be somewhat addressed to assess the limitations of the study and critique results.

 

Concerns with methods included weighting very different words with the same value (i.e. being a genius is apparently the same as having a knack for something), distribution of words used, and how words were categorized and what those categories meant. Re-doing the study as a double-blind would also help, as well as a more narrow choice of words in general (such words like “queen*” and “king*” seemed… excessive, and were – let’s hope – doubtful found in a single response.) Authors should have limited the words addressed by their analysis to those that may have actually been used by reviewers instead of what appears to be a standard list of YAY and NAY words. Also, pretty small sample size. Of course, as Beth Hellen (@PhdGeek) pointed out, it could be a pilot study. In any event, we agreed that the methods needed some work, but we’d all like someone versed in them to provide a better critique.

 

However, a note: My understanding was the words used did come from other, published studies and methodologies. Either way, there did appear to be a underlying bias in the words used – perhaps indicating a larger, systemic problem with the words we use to define people along the gender binary, and how we code and value those words. As Cheng H. Lee (@chenghlee) noted, “In perhaps not-so-subtle way, this could have incorporated broader biases about masculine vs feminine words into the analysis.”

 

Moving on to those “larger issues.” First and foremost, why would women be praised more than men? Especially given the increasing evidence that women are seen as less competent and are overlooked for jobs, tenure, even mentoring, and described using less capable words even by people trying to get them a job/money (e.g. in letters of rec)?

 

Given the findings argued by this study… What’s going on with grants?

 

Well. Perhaps we should be looking at it a bit differently. As Jonathan Goya (@jkgoya), the premise could be seen another way: “Do reviewers use different language to review women and men?” Ahhhh… now we’re getting somewhere…

 

For the first potential explanation, an old favorite of mine: Chivalry and the gender binary. Ladies be all soft and sensitive, duh, and, moreover, a true gentleman is not rude to ladies. Yes that’s an exaggeration, but you get my drift: Men used “nicer” language when speaking with women than with men.

 

Although… the women were also better funded, according to the study, so there’s less evidence that men were just being nice and letting the ladies down easy. That said, Jonathan Goya (@jkgoya) still noted “from personal [experience], I’m pretty sure men speak to each other in much more directly critical language than between men and women.” Also personally believing this to be true, I’m unwilling to throw out this explanation as a possibility. In addition, R. Deborah Overath (@scienceknitsteryes on that name) pointed out that, given how awesome the words were for women, they should actually have scored better.

 

Alternatively, as Ruth Hufbauer (@hufbauer) suggested, maybe men are becoming more aware of their biases and are overcompensating or being too careful… ?

 

Another explanation: The bar is lower for women. Many people are just surprised (surprised!) when women write a stellar grant proposal. They don’t expect it, so are more glowing in response. Moreover, Jonathan Goya noted “…to get the same scores, women have to really wow the reviewers” and Lauren Sakowski (@LaSaks87) reiterated that the women may have put in “extra effort for the same funding/recognition”.

 

Basically, we either don’t expect women to do well, or they have to put in the extra effort for the same recognition. Or both.

 

As some additional evident, Beth Hellen (@PhdGeek) noted that there is a larger difference between the positive and negative words used for funded women, but little difference for men. Perhaps the actual content of proposals from men somehow counted more. In addition, again to R. Deborah Overath’s (@scienceknitster) point that women possibly should have gotten better scores given the words used in their reviews. Perhaps the bias is not in the language used, but in the actual score that, you know, actually matters.

 

Of course, perhaps women just write better grants.

 

Or… they have more experience with them and exactly what reviewers are looking for. We all know grants can be formulaic. We also know women are less likely to be tenured or in leadership positions. Maybe these women have spent more time in soft-money jobs that simply require more grant writing to stay afloat in the world. Consequently, they’re just better at it.

 

Yet, again, as scientists assessing a study from a generally unfamiliar field, we craved more information. We speculated on additional variables that may help us piece apart the methods and the results, and really assess why this paper, on its surface, seems to contradict what more and more studies are telling us, and what many if not most of us know from experience: women are biased against in the sciences. We are still going up the stairs, when men have had an elevator.

 

 

Finally, Ruth Hufbauer reminds us that, yes, we’re scientist, but we’re also human. Just like the reviewers and the authors. It’s difficult to do things, like be on review panels, without either being biased in some way, or at least being worried about it.

 

This would be the final point I’d make, and I hope it’s one we come back to repeatedly in the Diversity Journal Club: As Dr. Wrasse (@labroides) asked: does a fish know it’s in water?

 

How do we recognize our own biases?

 

And what do we do about them when we start to figure them out? How do we deal with them in others?

 

That was where the Diversity Journal Club left off: contemplating how we become more self-aware, how we educate ourselves and others, and how we raise awareness.

 

We hope we’re doing our little part of this, in our own little corner of the twitterverse. Until next time, kids…

 

Lastly, a quick but very important note from Jonathan Goya and Beth Hellen that I was absolutely guilty of: avoid using karyotype (e.g. XX or XY) when discussing men or women. This automatically assumes sex, and negates a person’s right to self-identify their gender. Therefore, please instead use M, F or alternative. And please keep these critical hints coming!

 

 

The next Journal Club will be next week! We will post a paper on Monday 9/29 to review on Friday 10/3 at 11am EST. Have one we should read? Let us know! Since we just did one on gender, let’s have a new diversity topic for the next one – any and all welcome.

 

Thank you to all participants (and give them a follow, they’re awesome!)*

 

Doctor PMS (@Doctor_PMS) – the one who got us started with one little tweet!

Jonathan Goya (@jkgoya)

Dr. Wrasse (@labroides)

Beth Hellen (@PhdGeek)

biochem belle (@biochembelle)

Ruth Hufbauer (@hufbauer)

Mark (@NE14NaCl_aq)

PinkGlitteryBrain (@aiquintero)

Cheng H. Lee (@chenghlee)

Lauren Sakowski (@LaSaks87)

Deborah Overath (@scienceknitster)

Ian Street (@IHStreet)

Storify of the #DiversityJC

 

… and anyone else who checked in and followed the discussion. Again, we invite any and all participants, as long as you read the article and no trolling, please (although that just means we’ll ignore you. Which is a bummer. For you.)

 

‘Til next time!

 

Emily (@DrEmilySKlein)

 

*Let me know if I got any names wrong or you have trouble finding someone!

Twitter Journal Club discussion around #diversity in #STEM

Everything started last Friday when I cited an article from Science Magazine:

In sequence, we had a very interesting convo with @DrEmilySKlein and @jkgoya about the actual paper and had the idea to start a Journal Club on Twitter around #diversity in #STEM. The initial idea is to do it every other Friday at 11am EST. I gathered people interested in a Twitter list. Please contact us if you want your name to be added to the list.

Let’s make the difference! Join #DiversityJC and spread the word!

Here is the article for next week (09/19): http://journals.lww.com/academicmedicine/Abstract/publishahead/A_Quantitative_Linguistic_Analysis_of_National.98987.aspx