Web of Science Backfiles Illuminate a Dark Past, Underscoring Lessons on the Loss of Top Researchers

Web of Science Backfiles Illuminate a Dark Past, Underscoring Lessons on the Loss of Top Researchers
by Christopher King
Marketing Communications Manager, Scientific and Academic Research, Clarivate Analytics
Science Research Connect

Fabian Waldinger

Economist Fabian Waldinger was a graduate student, reading a book on the German education system, when the idea struck him. “A sentence in the book noted that, when the Nazis came to power in the 1930s, the rules they instituted resulted in the dismissal of 20 Nobel laureates from German universities,” he says. “And I thought, well, Germany hasn’t had 20 Nobel laureates after World War II, in the entire time period since then. That got me going, and I started to read more, and the more I read the more intrigued I became. And then I got very excited after learning that you could actually collect data on who was teaching at each of the universities and who was dismissed.”


For the last decade, Waldinger, now based at the London School of Economics (LSE), has been following up on that original insight. Along with accessing and digitizing detailed employment rosters from German universities dating back more than a century, Waldinger turned to another resource: Clarivate Analytics Web of Science™ and its backfiles that now cover publication and citation data back to the year 1900.


These tools have allowed Waldinger to explore a dark chapter in the history of academia: the dismissal by the Nazi government of more than 1,000 Jewish scientists, along with those deemed “politically unreliable, between 1933 and 1940.


Moreover, the addition of statistics from the Web of Science has permitted him to gauge the consequences of these personnel losses, in terms of productivity and impact, on the German institutions. As the displaced researchers – many of them top people in their fields – found their way to the United States, England, and other countries, their visibility and influence went with them.


For Waldinger, the historical scenario provides an ideal test bed. Every institution, of course, is subject to its own internal dynamics. Waldinger, meanwhile, has a particular interest in outside forces (or, to use his preferred term, “exogenous” factors) and their effects on institutions. It is hard to imagine more extreme exogenous forces than those at work in 1930s Germany. And yet, as Waldinger notes, his work goes beyond detached historical inquiry that has no bearing on today.


“I was inherently interested in the history,” he says, “and all this work started before the recent upheavals we’ve seen with Trump, Brexit, the dismissal of academics in Turkey, and so forth, but I think a lot of things we learn from this work can be applied today, at least qualitatively. Somehow it’s become more topical over time.”


Evaluating the “shocks”


In a 2010 paper, Waldinger examined the expulsion of mathematics professors in Germany and the subsequent effect on PhD students (F. Waldinger, Journal of Political Economy, 118 [4]: 787-831, 2010). Between 1933 and 1934, approximately 18% of mathematics professors were dismissed, including several world-renowned mathematicians. In establishing criteria for gauging university quality in the wake of this “exogenous shock,” Waldinger turned to Web of Science backfiles for the 1920s and 1930s in order to ascertain the productivity and impact of mathematics faculty, as well as to identify top-cited journals in the field.


By a range of measures – including student/faculty ratios, the likelihood of publishing one’s dissertation in a top journal, and employment prospects – Waldinger determined that departmental quality and outcomes for PhD students suffered as a result of these personnel losses.


A 2012 report also used Web of Science data and other measures to examine the effects of expelled faculty on those peers who remained – the “stayers,” as Waldinger calls them (F. Waldinger, Review of Economic Studies, 79 [2]: 838-61, 2012). Contrary to his expectation, Waldinger noted that, at least for established scholars, any local, negative effects of dismissed peers on the production of published papers were indiscernible.


For younger generations of scientists, however, the story is quite different, as the 2010 paper on mathematicians attests. Waldinger extended these findings in a 2016 report (F. Waldinger, Review of Economics and Statistics, 98 [5]: 811-31, 2016). In this study, along with precise accounting of expelled scientists, he added a second exogenous shock, by examining detailed tabulations of damage to German and Austrian universities from Allied bombing raids during World War II.


As he discovered, the physical/capital shock of bomb damage had far less effect than the human shock of losing professors – particularly “star” professors.  As Waldinger concludes in the text, “The previous results indicate that dismissal of scientists, especially high-quality ones, caused larger declines in output than the bombing of universities. Furthermore, the human capital shock was more persistent.” Specifically, in one finding, a 10 percent shock to human capital caused a reduction in output four times stronger than a 10 percent shock to physical capital.


“In that paper, I find very persistent and long-running effects of the dismissal of Jewish scientists, which effectively killed departments, even in the very long run,” says Waldinger. “Fifty years later, departments that lost people because the Nazis kicked them out were doing substantially worse than departments that did not lose people.”


One of the most damaging effects, Waldinger notes, is on the subsequent difficulty of hiring high-quality researchers. “Once you lose good people, and particularly once you lose superstars, the quality of hires collapses and does not recover. This may be because the departments can no longer identify good people, or because good people no longer want to go there.”


Although the effect on established researchers and their output may have been minimal – as Waldinger noted in his 2010 report – the consequences for young researchers were serious. Lacking the presence of accomplished, high-quality mentors, PhD students missed out on publishing opportunities, the forging of personal contacts, and other experiences crucial to the establishment of a solid academic career.


Exporting invention


Although mostly concentrating on the negative aspects of displaced researchers, Waldinger’s work has also touched on the opposite side of the phenomenon: the benefits that those researchers, after their enforced emigration, brought to their new institutions. In a 2014 study, Waldinger and colleagues examined rates of US patents flowing from fields in which German chemists had entered stateside institutions after leaving their native country (P. Moser, et al., American Economic Review, 104 [10]: 3222-55, 2014).  The authors noted that US patents increased 31 percent. Results suggested that this increase was due to the presence of the prestigious German researchers, attracting new talent and encouraging innovation.



Back, and to the future


In assessing the contemporary applicability of his work, Waldinger points to truths that appear to span the decades since the 1930s. In particular, as he notes: “The fact that superstars matter, and not only in universities. There’s some work by a colleague here at LSE who looks at inventor teams and patent data, and he also finds that the younger the inventor is, the more they’re affected by losing superstars on their team. So, the results in commercial firms are similar to what I find in the university sector. It makes a broader point about the contribution of high-skill individuals.”


Not content to confine themselves with exploring data from the 1930s, Waldinger and colleagues are extending their efforts back to 1900 and around the world, expanding their digitizing of faculty rosters. They also plan to match the personnel data to Web of Science figures on publication and citation, not only back to the turn of the 20th century but up to the present day. “We will have the whole network of the scientific community,” says Waldinger.


Ultimately, the plan is to tackle a range of larger questions. For one, he says, “We want to understand the birth of ideas: What characterizes the times and places from which important ideas emerge? What are the conditions needed for scientific revolutions to occur? We’re reaching the end of the digitization process for data for all professors in the world. So, very soon we will have, for every 10 to 15 years since 1900, a cross-section – a roster of university professors in all countries. And together with the Web of Science data, that will be an amazing resource.”



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