“Diversity breeds innovation” is a common adage. Science is no exception. Individuals that diversify science teams and organisations have experiences and insights that are distinctly valuable. They bring unique perspectives and come up with new ideas and innovations within existing thought structures. Such ideas and innovations in turn propel science forward into uncharted territories.
Yet, there is something markedly paradoxical about these claims. The scholars who would actually diversify academia, women and racial minorities, are the ones most heavily under-represented in professorships and research careers. If especially those individuals who diversify science teams or organisations are prone to innovate and advance science, why does academia persistently fail to reward them with successful careers? One possibility is that women and racial minorities innovate less, despite bringing diversity to their respective disciplines or departments. Another possibility is that diversity does breed innovation, but that diverse perspectives and ideas are less rewarded.
Which possibility holds up when confronted with data? In our , in the Proceedings of the National Academy of Sciences,?we identified and unraveled this paradox. We analysed the near-population of US PhD recipients. Three decades of US doctorates covering about 1 million graduate students and their dissertations. Through text analysis and machine learning, we identified the level of novelty and innovation of their dissertation texts and whether that correlated with their future scientific impact and faculty career.
What did we find out? We found evidence that women and racial minorities are more likely to introduce scientific novelty. And yet, the novelty they introduce was, on average, less likely to be rewarded: their ideas were used less often and were less likely to bring them influential faculty positions.
Part of the differences in PhD recipients’ scientific impact and career likelihoods seems to be due to the devaluation of gender and racial minorities’ ideas. This can be partly explained by their different models of thinking about problems or the different manner in which they bring ideas together.
How does such a dynamic arise? We acknowledge that there is proven racial and gender discrimination within science and wider academia that contributes to women and minorities having less successful careers.
But perhaps this dynamic also arises because science is a communal effort. As a community, it conforms to the pattern of its social structure. This means that majority groups – in this case white, male scientists – dominate central positions in communities, and their positioning places them closer to the core problems and discussions of science.
Moreover, it renders their understandings and framings of scientific problems more central and common to most other scholars. Well-positioned scholars are typically from majority groups and those traditionally represented rather than the historically under-represented. When scholars approach problems from distinct vantages and walkways, they bring new perspectives, and often ones the majority may see as atypical and struggle to make sense of, and this in turn leads to their devaluation.
Scientific innovation is an extremely important enterprise, especially in trying times like today where pandemics arise and where the legitimacy of science is questioned.
There are clearly scientific innovations arising that have objective value independent of the bias we find – vaccines and medical treatments, for example.
Our work merely shows that the scientific community and enterprise must constantly engage in self-critique and practice epistemological vigilance so as to improve its efforts. When innovation and scientific impact aligns with attributes such as gender or race, like we identify in our study, it raises questions as to the basis of scientific advancement and what can be done to improve that basis.
At present, a significant portion of scientific discovery is guided by attributional biases. Such differential valuation is counter to the scientific community’s notion of “facts” and it has long-lasting career implications for scientists themselves. It partly explains why we find fewer women and racial minorities in the professoriate.?
In turn, this reproduces stereotypes that professors are male and white, again possibly reinforcing differential valuation of ideas – white male ideas may be seen as more legitimate.
The patterns we identify in our study don’t invalidate the scientific enterprise. They do, however, subvert one of science’s key features: it shows why and where bias and subjective evaluation finds a foothold. But knowing why and where bias exists is the first step to correcting it.
Bas Hofstra is a postdoctoral research fellow and?Daniel A. McFarland is a professor at Stanford University.
