Persistence and Uncertainty in the Academic Career - New Trends in eHumanities

Alexander Petersen, IMT Lucca Institute for Advanced Studies, Lucca, Italy


April 26, 2012

Persistence and Uncertainty in the Academic Career
Understanding how institutional  changes within academia may affect the overall potential of science requires a better quantitative representation of how careers evolve over time. Since knowledge spillovers, cumulative advantage, competition, and collaboration are distinctive features of the academic profession, both the employment relationship and the procedures for assigning  recognition and allocating funding  should be designed to account for these factors. In this talk I will present recent research on the annual production $n_{i}(t)$ of a given scientist $i$ by analyzing  longitudinal career data for 200 leading scientists and 100 assistant professors from the physics community  (Petersen et al., PNAS 2012). We introduce a model of proportional growth with variable appraisal systems to better understand the evolution of careers in competitive systems. This theoretical model shows that short-term contracts can amplify the effects of competition and uncertainty making careers more vulnerable to early termination, not necessarily due to lack of individual talent and persistence, but because of random negative production shocks. I will also discuss team efficiency and the relationship between fluctuations in scientific production and a scientist’s collaboration radius, as well as the results of large-scale analyses of  productivity, impact, and longevity using empirical career data from thousands of academic and professional athlete careers (Petersen et al., PNAS 2011). This study uncovers a remarkably simple statistical law which describes the frequencies of the extremely short careers of `one-hit wonders’ as well as the extremely long careers of the `iron-horses’. Our model highlights the importance of early career development, showing that many careers are stunted by the relative disadvantage associated with inexperience.

I am currently an assistant professor at the IMT Lucca, and a member of the Economics and Institutional Change division and the Laboratory for the Analysis of Complex Economic Systems (AXES) research unit. Before joining the IMT, I spent my doctoral years at Boston University where I received my Ph. D. in Physics in May 2011 (Advisor: H. Eugene Stanley). My curricula and research have focused on the analysis of stochastic phenomena in the social and economic sciences using concepts and methods from statistical physics. I am currently involved in analyzing “big data” comprising (i) high-frequency Trades and Quotes (TAQ) financial data, (ii) Google n-gram data, and (iii) measures for longevity, success, productivity and innovation in science and professional sports. In the most broad sense, I search for statistical regularities in empirical data which can be used to better understand patterns of growth in diverse complex systems.

(Presentation slides)