by Janice Nigro
Blah blah blah…more studies performed to investigate gender disparity in science. We research the issues, we write about them, we even have to answer questions in our grants about them. But is it just talk or do we act on some of our rhetoric?
I have had some of my own questionable moments throughout my career at the bench, even in another country boasting of gender equality. Everywhere, drama often erupted ironically when I was most confident. I even once found myself in the awkward position of having to fight to keep a prestigious grant (500,000USD) that I had been awarded. It had been declined by my department, the very department that had authorized submission of the grant six months before.
While I didn’t want to believe the decision was directly related to my being a woman, I had to wonder whether it would have been an issue for a man at all. At the very least, I felt the so-called drama was indirectly related to my gender. I didn’t have a posse.
I recently started to think about my career in science after reading another report claiming this time that women were underrepresented in the field of genomics. I reacted strongly to this article because I felt the data were presented as if women were again failing at something. Based on my own experience, I wondered, exactly what do you have to do?
So I felt motivated to ask within my science network about what we do rather than what we don’t do and what might make gender disparity less of an issue in science.
My survey was not scientific. The group was small, but diverse. Women were of different races and some were working in other countries. Some work in companies, some work in academia, some run their own labs, and some have their own businesses. One of them had served as chair of a department.
All worked in biological sciences, including fields in cancer, immunology, and assay development. And many were deeply involved in genomics programs. All, including myself, enjoy conducting experiments. “Every mini mystery I solve leads to five more new ones,” one exclaimed even after 30 years in science.
I asked what they were most proud of in their careers, expecting answers about a specific result or paper. Responses however somehow mixed the personal with the professional. Or they cited an award that recognized their body of work.
Participants were more reluctant to divulge experiences potentially related to gender. It’s difficult, however, to pinpoint which events in a career are examples of our own individual failures, shortcomings, or other circumstances. “One does not like to attribute success, or lack thereof, to static measures such as gender,” as one of them said. One remarked on a blatant declaration by a professor in college, that women should not be engineers. But as another put it, “The problems today are not so overt as to warrant complaint. It’s just another issue you have to deal with.” Decision making for example might take place without you.
Are there any solutions for these issues? Education on unconscious bias gained some popularity when a study revealed that hiring faculty (whether male or female) tended to choose male over female applicants, even though their CVs contained the same content. A big effort on some US campuses, some participants mentioned, is to educate employees and leaders of departments who make critical decisions on hiring, about unconscious bias. Unconscious bias can impact all aspects of the work environment, even patient treatment. “It’s not much, but it’s a start,” one commented.
One of the women found direct interaction with other women to be empowering, and that “lean in” discussions brought about more scientific interaction. It was a good point, and I wondered if I was there for other women in science when it was my turn. How can it be so hard to encourage the ones who want to do the job? We might not be able to make a greater proportion of girls/women want to pursue a career in science, but we can certainly support the ones who already want to.
If you aren’t convinced that bias against people exists, bias against projects certainly exists. Not just as measured by our level of interest in a project, but also by our definition of productivity. Bias is inherent in the system. For example, is a PI who produces a lot of papers that are cited rarely (the exception being an obscure topic) more productive than one who produces few papers that are cited often? Since we tend to mark progress based largely on the number of papers published, especially in short time frames, we are not necessarily defining progress by the depth and difficulty of the project.
A key European PI in my field once told me that he didn’t think what he was doing was necessarily smart science, but his group was efficient at generating solid papers. He could see that the individuals in his lab performing smarter experiments, as he called them, suffered for it. In the long run, such experiments benefited the lab tremendously but not the individual.
Although gender disparity is often the target of discussions, women are likely to be just one type of measurable casualty in a system with bigger philosophical issues. With decreasing funds, competition has intensified. But defining what we mean by the best grants is still subjective and highly influenced by priority. The “best work” is not necessarily all encompassing based on the criteria we use to define it. What we think is so important today, might not be tomorrow, and we might be missing something when the criteria are formulaic. Non-conventional fields of interest are just as likely to yield breakthroughs. Scientists after all won the Nobel Prize for cloning green fluorescent protein from a simple creature, and CRISPR based on research in bacteria is even discussed in mainstream media.
We fool ourselves into being impressed by numbers. And yet, one of the interesting findings is that women in pursuit of higher risk career positions, although they tend to publish less, publish articles of higher impact in their field than their male counterparts.
A policy change that might help the kind of labs women tend to work in or run is the capping of funds issued by the National Institutes of Health for well-funded investigators. An argument against this approach is that funding should be reserved for the most successful labs. But we can’t always be sure that what we think today is even going to be important or right tomorrow. p53 was thought to be an oncogene for years before another lab performed a definitive functional experiment.
The diversity we crave in science is not just in hiring women vs men (or any minority vs anyone else) but in thinking. Currently 40% of funds support 10% of labs. Diversity is therefore vulnerable in the science we are doing as well as who is doing the science. It stands to reason that people of different backgrounds bring different perspectives. But if we tend to choose to work with people who think and act like us whether male or female (or any race or disposition), then we are not actually creating diversity.
I always felt in Norway, which functions as a social welfare state, they were missing a terrific opportunity to eliminate competitive science funding all together. I found it ironic that the government would not give me a grant to study human brain tumors, but they would give me unemployment (which was very reasonable). With this safety net, Norway should simply pay scientists to do their work and see what happens.
If we can learn anything from studies on gender disparity in science, it’s that scientists have different interests and different ways of achieving important goals. Genomics is only one discipline. The result, that only a single woman is running one of the top 20 genomics labs, might say more about where our interests lie than what our limitations are.
Big data producing genomics projects reveal important information, but let’s face it, today they are easy in concept and low risk experimentally. You don’t have to worry about a sequencing gel breaking at the last step, and you are sure to get a paper. It’s great if highly focused genomics labs also progress to more functional studies. If not, they really aren’t risking much, not today.
More functional projects are slow to develop so they might not do well under the current criteria used to award funding. No one in my group in Norway wanted to touch my project on low grade gliomas. There was no model system to study them, and I was working in a small country where samples of an already rare tumor type were thus even rarer. I gave all my heart to it, and it worked, but the project led to the death of my career at the bench. The project was not productive, i.e. not high volume paper producing. I felt vindicated ultimately as low grade gliomas gave us some incredible insight into the development of cancer.
As scientists, we learn to have an unbiased view of our data. “What does it tell us?” we ask. Our degrees declare doctor of philosophy in bold print. Bias in science then contradicts our basic training. So the drama is somewhat misdirected; the drama is what we discover and not so much who discovers it. Let’s just make discoveries.
Sometimes I think the solution is simple: let scientists do what they want. We do this with our own children. We simply give them opportunity. Hand them the tools, sit back, and let ourselves be amazed.
PS Thank you to all who were gracious enough to participate in my survey.
©Janice Marie Nigro/www.janikiInk.com
Looking for a scientific editor or writer? Contact Janice Nigro at Janice Nigro Scientific Editing and Writing. I have published in Cell, Science, and Nature, and articles I have edited have appeared in Cancer Research, PLoSONE, the Journal of Surgical Oncology, and Oncotarget.