Neil DeGrasse Tyson on "The Larry Summers question: What's up with chicks in science?":
From a panel discussion hosted by the Center for Inquiry. Starts at 1:02:30 of the video.
Neil DeGrasse Tyson on "The Larry Summers question: What's up with chicks in science?":
From a panel discussion hosted by the Center for Inquiry. Starts at 1:02:30 of the video.
Over at Tenure, She Wrote today:
For although it is true that Amy is a bit of a conceited twit, I strongly object to the core messages in this little speech: don’t show off, even if that means no-one notices how awesome you are. It’s better to be overlooked than to be conceited.
Although I don’t remember Sister Bear being particularly braggy, a quick Google search turned up several hits for “Braggy Sister Bear,” including some actual pages of Berenstain Bear books.
As you may be aware, I have a nonzero number of mini-women in my household. As a parent who is around a fair number of both boys and girls in the elementary and secondary school ages I am constantly amazed. The level of organization, responsibility, on-task behavior....it is like they are different species. My wife or I remark to each other on at least a weekly basis "Why are men in charge again?"
The above mentioned blog entry may be relevant to the question so Go Read.
This guest post is from @iGrrrl, a grant writing consultant. I think I first ran across her in the comments over at writedit's place, you may have as well. She brings a slightly different, and highly valuable, perspective to the table.
For those who have been worrying about their own grant applications, the Ginther report detailed the relationship of race and ethnicity to NIH grant funding at the R01 level, and NIH has created a few initiatives to try to change the pattern of lower success rates for African American applicants. In early April, the applications are due for the Building Infrastructure Leading to Diversity (BUILD) Initiative, which would fund large-scale projects within individual institutions, and the NIH National Research Mentoring Network (NRMN), which is designed to build a network of mentors. In other words, diversity interventions writ large, with millions of dollars behind them.
The NSF ADVANCE program started in a similar way, and some of the early ADVANCE projects included programs with a limited evidence base. The successes of components of these programs were variable, and the recent RFA included a social science research component to complement the required evaluation of ADVANCE-funded activity. It started with good intentions, and eventually became clear that more than good intentions were needed. Part of the NRMN announcement calls for pilot programs, but I would argue that in the first year, the network should do the social science work to consolidate the anecdotes African Americans tell about their mentoring experiences into hard data, so that the pilot programs can be based upon addressing the needs identified by African Americans who have been through, or training right now in, the current system.
At the recent AAAS meeting in Chicago there were sessions on building diversity in science. At one I learned that explicit bias has reduced in the last 30 years, but implicit bias hasn't. We think we have made progress, and that our conscious intentions are enough. But they clearly are not. Expecting trainees to overcome biased behaviors (to which the actors are blind) places an undue burden on those who are discriminated against. There are studies showing that education about implicit bias helps to reduce such biased behavior, but education attempts can also be done badly and backfire. As pointed out in a recent piece in Science by Moss-Racusin, et al., there is an evidence base now for doing intervention well. If NIH is putting money into large-scale intervention, I hope the existing science will be part of the applications, and expected by the reviewers.
I've spent a lot of my professional life working on exactly the kind of large, infrastructure-based grant application represented by the BUILD and NRMN programs. It is easy for PIs to make assumptions that interventions that sound good on paper will actually have any impact. My concern is that what will be proposed by the applicants to BUILD and NRMN may miss the strong social science work that exists, and that still needs to be done. In fact, some of the best research on effective mentoring is the business literature, a place where few biomedical scientists would think to look.
Grant applications shouldn't be pure fiction, but based on solid evidence. Every grant application represents a possibility, a reality, that could come to pass if the funds are awarded. In the mentoring literature, practices that improve the success for African Americans are often shown to improve the climate for everyone. There is an opportunity here for those in biomedicine to learn from other fields, to consider an evidence base that is outside their usual ken, and to improve the entire biomedical enterprise by improving the overall environment. I hope that those applying for BUILD and the NRMN include the social sciences, and even more importantly, include the voices and ideas of the very people these programs are meant to serve.
NIH has a long history of using dollars to encourage cultural change, with mixed results, because applicants can have varying levels of commitment to the NIH vision while being happy to take NIH dollars. The ADVANCE program at NSF had some hiccups as they worked out what worked to improve the climate for women in STEM. The leadership teams for BUILD and NRMN should include people with a deep knowledge of the research and scholarship on bias and on mentoring, and who can do the rigorous analysis of the current state of affairs for African Americans in biomedical science. I hope I'm wrong here in worrying that such people won't be included, but I've seen fiction in grant applications a few too many times.
Dr. Jean A. King [webpage] is Vice-Chair of Research and Professor in the Department of Psychiatry at the University of Massachusetts Medical School [PubMed; CV]. She completed her PhD in 1988 at NYU in Neurophysiology and conducted postdoctoral training at Emory. Dr. King's research record is diverse but can be characterized as focusing on neuroendocrine systems, stress, aggression, fear and substance abuse. Her work has also focused on advancing noninvasive imaging techniques in animal models using magnetic resonance imaging, in addition to the papers she has credit on three patents for neuroimaging advances. Professor King is the Director of the Center for Comparative Neuroimaging within the UMass Medical School. A recent paper from her laboratory (open access) applies imaging techniques to investigate white matter structural integrity in the brains of nicotine addicted human subjects that are associated with measures of physical dependence.
Over the years Dr. King's work has been funded by the National Science Foundation and the National Institutes of Health (a RePORTER search illustrates her NIH funding history as a Principal Investigator).
As you would expect for a scientist of this caliber, her expertise has been sought by an array of journals to provide peer review of manuscripts and by the NIH to serve on many grant review panels. I can confirm that Professor King is an excellent and insightful reviewer of grant applications with a persuasive and often humorous demeanor. Her comments were invariable informative, particularly for noob-ish grant reviewers (ahem). Similarly, Dr. King has supervised numerous trainees, participated on many service committees for her University, for the NIH and for multiple academic societies or entities. She has additional service in nonacademic settings. In this record there is a strong addition of service on issues important to women in science and in careers, generally.
I thank you, Professor Jean A King, for your long commitment to advancing our understanding of the brain and of affective disorder.
Disclaimer: I am professionally acquainted with Dr. King.
picture borrowed from http://www.umassmed.edu/Content.aspx?id=96786
Series Note: The Diversity in Science Blog Carnival was created by D.N. Lee of the Urban Science Adventures! blog. In early 2009 she issued a call for a new blog carnival celebrating diversity in science and hosted the inaugural edition. The Diversity in Science Carnival #2 was hosted at Thus Spake Zuska under the theme Women Achievers in STEM - Past and Present. Prior entries from me have focused on Laura O'Dell, Carl Hart, Chana Akins, Percy Julian, Jean Lud Cadet, and Yasmin Hurd.
Huh. A bit surprised I never had occasion to repost this. Well, the conversation about the Ginther report and disparity in NIH Grant success reminded me of this.
Originally posted 03/23/09.
In the year 1899 an American cyclist won the world championship in the 1-mile track event. In those days, track cycling was what really mattered and cycling was a reasonably big deal. So this was an event in sport. An even bigger deal was the fact that Marshall "Major" Taylor (Wikipedia) was black. This fact was, likewise, important:
The League of American Wheelmen, then the governing body for the sport, banned blacks from amateur racing in 1894, just as bicycling's popularity surged.
Jeremy Berg made a comment
If you look at the data in the Ginther report, the biggest difference for African-American applicants is the percentage of "not discussed" applications. For African-Americans, 691/1149 =60.0% of the applications were not discussed whereas for Whites, 23,437/58,124 =40% were not discussed (see supplementary material to the paper). The actual funding curves (funding probability as a function of priority score) are quite similar (Supplementary Figure S1). If applications are not discussed, program has very little ability to make a case for funding, even if this were to be deemed good policy.
that irritated me because it sounds like yet another version of the feigned-helpless response of the NIH on this topic. It also made me take a look at some numbers and bench race my proposal that the NIH should, right away, simply pick up enough applications from African American PIs to equalize success rates. Just as they have so clearly done, historically, for Early Stage Investigators and very likely done for woman PIs.
Here's the S1 figure from Ginther et al, 2011:
[In the below analysis I am eyeballing the probabilities for illustration's sake. If I'm off by a point or two this is immaterial to the the overall thrust of the argument.]
My knee jerk response to Berg's comment is that there are plenty of African-American PI's applications available for pickup. As in, far more than would be required to make up the aggregate success rate discrepancy (which was about 10% in award probability). So talking about the triage rate is a distraction (but see below for more on that).
There is a risk here of falling into the Privilege-Thinking, i.e. that we cannot possible countenance any redress of discrimination that, gasp, puts the previously underrepresented group above the well represented groups even by the smallest smidge. But looking at Supplementary Fig1 from Gither, and keeping in mind that the African American PI application number is only 2% of the White applications, we can figure out that a substantial effect on African American PI's award probability would cause only an imperceptible change in that for White PI applications. And there's an amazing sweetener....merit.
Looking at the award probability graph from S1 of Ginther, we note that there are some 15% of the African-American PI's grants scoring in the 175 bin (old scoring method, youngsters) that were not funded. About 55-56% of all ethnic/racial category grants in the next higher (worse) scoring bin were funded. So if Program picks up more of the better scoring applications from African American PIs (175 bin) at the expense of the worse scoring applications of White PIs (200 bin), we have actually ENHANCED MERIT of the total population of funded grants. Right? Win/Win.
So if we were to follow my suggestion, what would be the relative impact? Well thanks to the 2% ratio of African-American to White PI apps, it works like this:
Take the 175 scoring bin in which about 88% of white PIs and 85% of AA PIs were successful. Take a round number of 1,000 apps in that scoring bin (for didactic purposes, also ignoring the other ethnicities) and you get a 980/20 White/African-AmericanPI ratio of apps. In that 175 bin we'd need 3 more African-American PI apps funded to get to 100%. In the next higher (worse) scoring bin (200 score), about 56% of White PI apps were funded. Taking three from this bin and awarding three more AA PI awards in the next better scoring bin would plunge the White PI award probability from 56% to 55.7%. Whoa, belt up cowboy.
Moving down the curve with the same logic, we find in the 200 score bin that there are about 9 AA PI applications needed to put the 200 score bin to 100%. Looking down to the next worse scoring bin (225) and pulling these 9 apps from white PIs we end up changing the award probability for these apps from 22% to ..wait for it..... 20.8%.
And so on.
(And actually, the percentage changes would be smaller in reality because there is typically not a flat distribution across these bins and there are very likely more applications in each worse-scoring bin compared to the next better-scoring bin. I assumed 1,000 in each bin for my example.)
Another way to look at this issue is to take Berg's triage numbers from above. To move to 40% triage rate for the African-AmericanPI applications, we need to shift 20% (230 applications) into the discussed pile. This represents a whopping 0.4% of the White PI apps being shifted onto the triage pile to keep the numbers discussed the same.
These are entirely trivial numbers in terms of the "hit" to the chances of White PIs and yet you could easily equalize the success rate or award probability for African-American PIs.
It is even more astounding that this could be done by picking up African-American PI applications that scored better than the White PI applications that would go unfunded to make up the difference.
Tell me how this is not a no-brainer for the NIH?
In case my comment never makes it out of moderation at RockTalk....
Interesting to contrast your Big Data and BRAINI approaches with your one for diversity. Try switching those around…”establish a forum..blah, blah…in partnership…blah, blah..to engage” in Big Data. Can’t you hear the outraged howling about what a joke of an effort that would be? It is embarrassing that the NIH has chosen to kick the can down the road and hide behind fake-helplessness when it comes to enhancing diversity. In the case of BRAINI, BigData and yes, discrimination against a particular class of PI applicants (the young) the NIH fixes things with hard money- awards for research projects. Why does it draw back when it comes to fixing the inequality of grant awards identified in Ginther?
When you face up to the reasons why you are in full cry and issuing real, R01 NGA solutions for the dismal plight of ESIs and doing nothing similar for underrepresented PIs then you will understand why the Ginther report found what it did.
ESIs continue, at least six years on, to benefit from payline breaks and pickups. You trumpet this behavior as a wonderful thing. Why are you not doing the same to redress the discrimination against underrepresented PIs? How is it different?
The Ginther bombshell dropped in August of 2011. There has been plenty of time to put in real, effective fixes. The numbers are such that the NIH would have had to fund mere handfuls of new grants to ensure success rate parity. And they could still do all the can-kicking, ineffectual hand waving stuff as well.
And what about you, o transitioning scientists complaining about an "unfair" NIH system stacked against the young? Is your complaint really about fairness? Or is it really about your own personal success?
If it is a principled stand, you should be name dropping Ginther as often as you do the fabled "42 years before first R01" stat.
Next time you are at your favorite scientific meeting, take a look at the trainees that are standing forlornly, uncomfortably alone at their posters. Contrast them with the young trainees that have an audience stacked three deep in a semicircle.
Do you notice any differentials in male/female, attractive/unattractive, white/black/asian/latino/etc ?
I think I shall engage in this exercise at the upcoming meeting of the Society for Neuroscience in November.
Every black staff person in this hotel has now found me to tell me they were proud I was on the stage. That's why I show up.
— tressie mc (@tressiemcphd) October 14, 2013
reminds me of a post I wrote some time ago that encapsulates my position on underrepresentation in science, affirmative action strategies, etc. It is informed by my participation on diversity-in-academia committees at every level so far from undergraduate, to graduate student and as a faculty member. It is also informed by seeing the nitty-gritty of affirmative action decision making when it comes to the hiring of faculty (the "Dean's Hire", etc), the treatment of said faculty once hired and the outcome (tenure/denied) of such faculty.
It is also a position that I take in reaction to anyone who goes on about how skin-reflectance based affirmative action policies are bad because it may select individuals for whom this is their only apparent handicap in academia. Thereby overlooking people who don't share that particular handicap but otherwise beat out this person in the Oppression Olympics. Also my response to people who think that socio-economic lack of privilege is the only justifiable motivation for affirmative action policies.
This originally went up Aug 29, 2008.
This reminds me of a phenomenon experienced by a scientist with whom I am familiar.
"The conversation usually ends with 'Thanks Doc, it means a lot'."
It is no news that US research science looks like a little bit of apartheid. White folks are overrepresented in the faculty ranks and overrepresented in the trainee ranks down to the undergraduate level, relative to the general US population. Frequently enough relative to local city or state populations as well. African-Americans and Latino-Americans are considerably underrepresented. [Don't yeah-but me with your favorite allegedly overrepresented group in the comments, it is irrelevant to today's discussion.]
In the service ranks, this is a different story. Visit a few Universities around the country, attend scientific meetings in the usual hotspots of Washington DC, New Orleans, Atlanta, San Diego, Los Angeles, Chicago and unless you are in complete denial or completely oblivious you notice something. African-Americans and Latino-Americans (and some additional nonwhite ethnic groups) are considerably overrepresented in the service ranks. Administrative assistants, janitors, animal care techs, facilities staff, hotel and convention staff..you name it. These national realities are not just anecdotes, of course. Every time we talk about affirmative action issues in the Academy on a national level, the dismal stats are related.
I make my views on casting a wide net and dismantling artificial barriers to success in science pretty clear in my blogging. I argue this both from the perspective of an advocate for my scientific domain who wants progress made and as an advocate for the individual scientist and his/her career.
Michelle Obama and the scientist who receives the "Thanks Doc" conversations remind me of another important, perhaps more important, reason for dismantling artificial barriers to science career success.
It matters that "people who look like me, are like me, have families like me" are a highly visible part of the landscape. It matters a lot. And this is why I will smack down knuckleheads who bleat on about quotas and "taking slots from the more deserving" and crap like that. First, of course, because those types (almost hysterically, unbelievably, overrepresented in the fizzycyst population) display a fundamental intuitive misunderstanding of populations, central tendencies, variance in the distribution and the rarity of extreme talents. Second, because they disingenuously ignore the warm fuzzies, opportunities and biases associated with the vast majority of the Academy looking just like them. Third because these morally shriveled little wankers are just plain fun to tweak and can be tangled up in their inconsistencies and hypocrisy with little effort. But I digress.
Unsurprisingly, the scientist to whom I am referring looks somewhat other than the vast majority of independent scientists at the University in question. Actually, I think people have a fairly difficult time discerning just what ethnic association fits but lets just say "nonwhite", pointedly underrepresented in science. Of a variety with which many people who work in support roles at the University in question identify. Ethnicity pegging is not helped in that this person does not speak, act, associate, recreate, hobby-ate, idea-ate, iPod-ate, etc in any particularly ethnically-specific or stereotypic ways that I can detect. This observation is quite important. Unlike Michelle Obama, for whom many aspects of the identity package are consistent with the women being interviewed on the radio this week, this scientist basically only looks "like them".
My subject scientist relates numerous conversations which follow a common thread. Some staff person will drop by the office to say "Thanks Doc. It's really important to see one of us in this office doing this job."
That is the crux of the issue. Image is important. Identity is important. It matters to the larger issues of diversity that we have readily apparent, quotidian, barebones diversity. It matters to our social fabric of opportunity and fairness. It matters to the fundamental principles of what it means to be an American citizen when we are talking politics. It matters to the fundamental principles of the Academy as well.
Underrepresented Imposter Syndrome (no, something slightly different).
In the 23andOneQuarterMe era of percentiled ancestry, affirmative action policies should score on number of generations in Appalachia, percent of recent ancestors who never left the holla', percent African ancestry, Neandertal and what not.