The Nobel Prize gender gap

Author: Stephanie Kovalchik

This week, as the six recipients of Nobel Prizes in science take the podium, some might wonder what the absence of women among the awardees says about the state of women in science. It will be a fitting occasion for such reflections as the Nobel ceremonies will coincide with the 99th anniversary of Marie Curie's award in chemistry. For her contributions to the theory of radioactivity and her studies on the therapeutic properties of radium, Curie became the first woman to be honored by the Nobel committee, which gave her the Prize in Physics in 1903, and the only woman to receive the honor twice. Her place in history is made more special by the fact that these accomplishments came at a time when few women were able to enter the scientific profession.

If, in the early 20th century, there was a general belief that women were less capable of doing valuable scientific work than men, the quantity and impact of Marie Curie's research provided a strong counterargument. Some feminist historians have seen Curie's accomplishments as a symptom of the excessive demands women scientists faced throughout history; her extraordinary contributions, they argue, demonstrate that female scientists have generally been held to a higher standard than their male colleagues; women scientists have gained general acceptance only after above-average performance (McGrayne 2001, Wyer 2001). To support these claims, historians often return to the Nobel and highlight statistics suggestive of gender disparities in how the committee has recognized scientific achievement in the past. Over the 109 years of the Nobel's history, only 16 women have been acknowledged in the science categories (2 in Physics, 4 in Chemistry, and 10 in Medicine). Of these 16, 9 (56%) received the honor after 1980. Feminist readings of these figures conclude that the Nobel committee has largely neglected the contributions of women in science during the 20th century, with the gender gap narrowing only in recent decades.

Having raised the issue of gender politics, statistically-minded readers might recall that it was 40 years after Curie's second Nobel that Simpson published a paper describing a curious phenomenon in association analysis. The phenomenon, which came to be known as Simpson's paradox, occurs when an overall association between two categorical variables, female gender and Nobel recipient, for example, have no, or even a reverse, association when assessed within subgroups defined by a third factor. This statistical artifact was famously demonstrated in a case of suspected gender discrimination against female students applying to graduate school. The case study is relevant to the present discussion in more than its subject matter because it reveals a fundamental flaw in standard feminist readings of the Nobel data.

In the 1970s, an investigation of the admission rates to graduate programs at the University of California Berkeley (UCB) showed an overall significantly lower probability of admission for female applicants than male applicants. This led to the suspicion of pervasive bias in the admissions process whereby qualified female candidates were being systematically excluded from graduate study on the basis of their sex. Further analysis revealed a more complex story. When the association between gender and application acceptance was analyzed by department, it was found that the overall association in favor of males was, for the most part, an artifact of Simpson's paradox. The department-by-department assessment was not a story of gender bias but of an ambitious pool of female applicants who, in contrast to their more laid-back male peers, were disproportionally vying for spots in the most competitive programs. Had the interplay between gender, program preference and selectivity been overlooked, it might have resulted in an erroneous accusation of University-wide sex discrimination.

Judgments about the Nobel data that look only at the award counts make a similar mistake as the initial analysis of the Berkeley admissions data. The overall low acceptance rate for the female applicants to UCB would have only been evidence of bias if an equal proportion of male and female applicants were applying to each department. Similarly, the paucity of Nobel awardees would only be surprising if it was inconsistent with the proportion of women among eligible candidates, in this case, professional scientists.

Trends of Female Proportion of Nobel Prize Winners in Science from 1901 to 2010. By author.

Figure 1. Female proportion of Nobel Prize winners in science compared to proportion of women scientists.

To accurately address the hypothesis that science done by women has been persistently devalued in the past century, we need to consider trends in the representation of women among active scientists. To do this, I randomly sampled general science articles from the JSTOR database and determined the proportion of male contributing authors for each decade of the past 110 years. Taking into account the gender distribution of professional scientists with this method, the Nobel data tell a quite different story than the simple counts would suggest. For a selection process that is not influenced by a candidate's gender, the proportion of female Nobel winners should be comparable to the proportion of working women scientists. This was the case up to the 1970s (Figure 1), with a possible discrepancy in the decade following WWII, which could reflect a voting committee heavily influenced by the political climate of the time (for more on this topic, see Danny Dorling's article in the September 2010 issue (7.3) of Significance).

More recently, a gender gap has emerged as the number of female recipients has declined while the growth of women in the scientific profession has risen. The evidence suggests that, in the first half of the 20th century, qualified women were struggling to enter the scientific profession but those who broke through were as valued as their male colleagues. In more recent decades, the increasing rate of entry into the professional field reflects the victories won in combating barriers to a career in science (For a recent popular text on these changes see The Madame Curie Complex). Yet the widening gender gap for Nobel nods suggests that the average professional impact among the growing segment of women scientists, as a consequence of discriminatory or other factors, might not be keeping pace.

Trends in female proportion of Nobel Prize winners in Literature from 1901 to 2010. By author.

Figure 2. Female proportion of Nobel Prize winners in Literature compared to proportion of female authors.

Interestingly, the standard feminist reading of the Nobel awards in science is a better description of the trends for the Literature category (Figure 2). Based on the ratio of female to male bestselling novelists, as tabulated by Publisher's Weekly, women have held a nearly even place (40%) among professional writers in the 20th century. Despite this, the decennial proportion of female Nobel recipients has only begun to approach this level in the past two decades. Before the 1990s the percentage of female prize winners in literature was 7%, an astonishing difference of over 30%. Women writers have good reason to protest against the Nobel foundation for routinely neglecting the merits of their work.

Of course, what Nobel Prize trends say about the general opinion of the prize's respective fields is as mysterious as the foundation's voting process. But the even greater mystery, in the admittedly prejudiced opinion of this author, is why the Nobel committee, in its near-110 year history, has yet to name a Laureate in statistics.



  • Bickel, P., Hammel, E. A., O'Connell, J.W. (1975), Sex Bias in Graduate Admissions: Data from Berkeley, Science, 187, 398-404.
  • Jardins, Julie Des (2010). The Madame Curie Complex: The Hidden History of Women in Science, Feminist Press.
  • McGrayne, Sharon Bertsch (2001). Nobel Prize Women in Science: Their Lives, Struggles and Momentous Discoveries, National Academy Press.
  • Simpson, E. H. (1951), The Interpretation of Interaction in Contingency Tables, Journal of the Royal Statistical Society, Ser. B,13, 238-241.
  • Wyer, Mary (2001). Women, Science, and Technology: A Reader in Feminist Science Studies, Routledge.

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Hello, what are the names of the scientists who won the nobel prize for their work. 

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Stephanie Kovalchik


You are correct that the interpretation of the Berkeley admissions data by department is complex. Simpson's paradox manifested in inconsistent associations within department. It was not simply that no gender association was found across departments. The self-selection of applicants makes it difficult to assess the presence of a within-department gender bias, still the heterogeneity of the sex and application acceptance associations would seem to rule out a campus-wide bias disfavoring females.

Nobel Prize winners in science have traditionally been researchers that have made a path-breaking discovery: radioactivity, the double helix of DNA, the catalytic properties of RNA, etc. Compared to the physical sciences, defining "discovery" for analytical sciences such as economics, mathematics and statistics is complicated. Perhaps this is why we can still debate whether Gauss or Laplace discovered the normal distribution. What does finding a probability distribution actually mean when it is pure abstraction? It cannot been seen by a microscope or inferred with X-ray diffraction. Leading thinkers in the analytical sciences have really been inventors and the Nobel committee has historically been less impressed by invention than discovery. Somewhat ironic considering that, aside from the foundation bearing his name, Alfred Nobel is best known as the inventor of dynamite.

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HI Stephanie,

There is a contentious situation since the recent financial crisis whether the "Nobel" for economics ought to be withdrawn. This is not the position of the Nobel committee but critics of economists. In my view, the critics may be onto something.

But to get to the innards of your post, as you rightly note, the Bickel study has been criticized. While the results could be for the reasons you state, competitiveness, it could also be due to easier entrance requirements, which some critics have claimed as the reason for the disparity, although this would not be my position. The data is ambiguous on this.

If you look across all departments, one department could be interpreted as primarily contributing to the paradox though the number of female applicants was small compared to the number of males. And in one department, more than twice the number of females than males applied, and although the percentage of males admitted was greater than the number of females, the number of females admitted outnumbered the males by two to one. So, while one department may have been biased in one direction, another could have been biased in another with the biases canceling out overall, almost. Which is what Freedman showed in his critique of the study.

As for whether there ought to be a Nobel for statistics, one could argue that this would be inconsistent with the spirit of the other science Nobels, although they now give one for economics, recently a highly contentious issue. One also mustn't forget that the Nobel committee awarded Kissinger the Peace Prize. Mathematics has the Field medal which is just as prestigious as the Nobel. Should statisticians want a Nobel?

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Stephanie Kovalchik


Yes, defining the real candidate pool for the Nobel is tricky. I have considered actively publishing scientists to try to determine the ratio of male to female among the population of individuals competing for the Nobel, that is, those who, without a gender bias, would have a shot at getting a Nobel nod. But really it is a small portion of this group, those whose work has the highest impact. So maybe looking at the gender ratio among authors of high-impact papers? What measure of recognition would you suggest for defining the Nobel candidate pool?

In any case, any refinement of this kind will likely result in a more skewed distribution, favoring males, making the Nobel awards more consistent with the prospective awardees. Again, suggesting, that any bias that might be present in the prize winners is occurring at some earlier stage of the multistage process--from education, professional work, acclaim--that leads to the pool of Nobel hopefuls.

Since there is still a debate among some about whether Statistics is even a science in its own right, it would be hasty to make a short list for a Nobel prize in statistics. Still, I can state, with confidence, that women have had an important role in the advance of the field and the promotion of statistical thinking. Early examples: Ada Byron, Gertrude Cox, Florence Nightingale. More recently, female statisticians whose work has influenced my own education and research include Nan Laird, Rebecca DerSimonian, Annette Dobson, and Deborah Nolan.

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Thanks Stephanie for your very interesting post. As you say, it is important to define the pool from which Nobel prizewinners are drawn. The Nobel names are not drawn from the total pool of professional scientists, but only from those who achieve something outstanding (as nominated by their peers). This pool may not be representative because:

- some people (men and women) may have made significant advances which are not yet recognised or understood, or are deemed politically incorrect

- some people - and women in particular I would say fall into this category - have all the potential to reach the top of their scientific profession but do not realise this because of domestic responsibilities and the way scientific careers are structured

More women are entering science careers, but few make it to the top, and it is saddening that women seem to be under-represented with regard to the Nobel prize.

Which woman statistican would you nominate?

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