Diversity in science

How can we ensure that minority backgrounds are fairly represented in science?
15 December 2016

Interview with 

Kenny Gibbs, National Institute of General Medical Sciences


How can we ensure that minority backgrounds are fairly represented in science?


It's often claimed that certain groups are under-represented in the workplace, but what do the numbers say? And, in particular, what do they say about science? Kenny Gibbs describes what he's found to Chris Smith...

Kenny - My name is Kenny Gibbs. I am a program director at the National Institute of General Medical Sciences which is part of the National Institute of Health. I work in the division of training, workforce development, and diversity. Broadly, within the scientific community, there has been a longstanding challenge. How do we assure that our scientific community is able to cultivate and utilise talent from as diverse a pool as possible as it relates to gender, relates to ethnicity, people with disability, etc. so we set out to explore a few different things. Particularly, in the United States, there has been a lot of issues around again, diversity in the scientific research workforce and because most of the scientific researchers that are in academia, think about the diversity of the faculty. So, I want to do a couple of things. One: provide a systematic and quantitative view on what has been happening in our system over the last 35 years or so and then how do we use that to build a model to simulate where we might want to intervene as a scientific community to assure that we can enhance diversity in the research workforce in the provisory specifically. And we were looking in medical school basic science department mainly because we had access to a high-quality comprehensive data to double AMC faculty roster.

Chris - What is happening?

Kenny - As it relates to the talent pool, we see that there's been a really significant increase in the talent pool of scientists from historically underrepresented minority background that would black African-American, Hispanic, or Latino or Latina, Native American Alaskan native, compared to their peers from other backgrounds, we call them well-represented backgrounds. And so, we see that from 1980 to about 2014, there's a 9-fold increase in the annual number of PhDs from underrepresented minority backgrounds, graduating each year close to 900 a year whereas the faculty from underrepresented minority background particularly the basic science departments only grew at about 2.6 fold and so, we see much greater growth for underrepresented minority PhD pool welted to the assistant professor pool. This is in contrast to what we see for scientists from well-represented backgrounds where the growth of those two populations is more in line. The next thing that we see is that there's a broad light of connection between that talent pool and academic hiring. I think one piece that was pretty striking was that over the last decade, there were close to 6,000 scientists from underrepresented minority backgrounds who got PhDs in the biomedical sciences but there were 6 fewer assistant professors in these basic science departments. And so, we had close to 6,000 PhDs or were losing the population of junior faculty who will be the next generation of scientific leaders.

Chris - So, you're making lots of potential people to step into those post. None of them are finding places in these institutions in those posts. Why do you think that is?

Kenny - Exactly multifactorial. There could be differences in terms of the interest of scientists from underrepresented backgrounds versus the well-presented peers. Are there issues in the culture? Are there issues in the climate? Are people not part of the correct social networks? And then once we had people who actually decide to pursue those careers, there's a fair amount of evidence that there are a number of different biases that exists that can influence what happens that relates to progressing from the talent pool to academic hiring.

Chris - What can we actually do to change this and rather than just guess and then wait another 20 years to see whether or not we made the right choice. Are there any ways that we can bring the huge dataset that you have access to and some modern technology to bare and untry and crack this nut?

Kenny - Exactly. I think it’s a great question. What we have tried to do historically to say, when a lot of these diversity efforts started, there was really not an adequate talent pool. And so, we spent a lot of effort building that talent which we see has been effective. Well we’ve done to say, “Okay, now let’s use a modelling technology, a system dynamics model to test three approaches. One, let’s see if we just need to keep building a talent pool in isolation if that would get us there. Two, we recognise that the academic career landscape is a bit challenging at the moment. And so maybe it’s a function of just a broader labour market stress. Or three, maybe it is the function of a post-doctoral transition in academic hiring that need to be addressed.” And so, we use a system dynamics model to test those three approaches. What the model shows us is that the community needs to focus on postdoctoral transitions and academic hiring. And so, once we have this great talent pool which we do have at the PhD level, there needs to be a focus on assuring these people are in high-quality postdocs that they didn’t transition onto the market and are hired. A large pool in of itself is not enough. More faculty job in and of themselves are not enough. I think one that’s particularly interesting in a model is that we made sure that the system was on in which there was not active discrimination or biased. And so, even in that case, the model predicts that there's not going to be a substance of change through the year 2018. Even with we had 70 % minority PhDs, we still would have less than 10 % minority faculty. And so, I think it helps us to say that we don’t have to have malice or ill intent to have this kind of disconnect. It’s just a system architecture thing that we’d be thinking about more concretely how do we focus on those post-doctoral transitions and then making sure of the hiring practices online to identify and then cultivate this talent.

Chris - Would not the people who were getting those jobs at the moment turn around and say, “Well, I've worked hard too”?

Kenny - Yeah. I think everybody works hard. And so, the question sometimes is, why diversity? Then I say, “Well, why not?” Why wouldn’t we want the broadest pool of qualified people tackling these tough challenges? What I'm saying, the result is just saying that we actually have a large pool of talented and qualified people that for some reason are not making those connections. And so, we have been thinking about how do we assure those connections are being made and we know that diversity in many respects is critical to scientific excellence, the groups have more diversity, tend to ask broader questions, and play a lot of variety of approaches, and ultimately, go on leading to newer types of innovations. So there's nothing against the people who’ve gotten those jobs. It’s just to say, “Hey listen! Make sure that we have a full and fair competition.” And it seems to be at the moment, there is some disconnect which is not allowing us to have as robust the competition as we might want.


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