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We draw upon diverse datasets to compare the institutional organizational of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations(More)
We introduce a model of proportional growth to explain the distribution P(g)(g) of business-firm growth rates. The model predicts that P(g)(g) is exponential in the central part and depicts an asymptotic power-law behavior in the tails with an exponent zeta = 3. Because of data limitations, previous studies in this field have been focusing exclusively on(More)
Understanding how institutional changes within academia may affect the overall potential of science requires a better quantitative representation of how careers evolve over time. Because knowledge spillovers, cumulative advantage, competition, and collaboration are distinctive features of the academic profession, both the employment relationship and the(More)
Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research(More)
We refer to the framework developed by Ijiri and Simon (1977) and to the notion of independent submarkets (Sutton 1998) to provide a simple candidate explanation for the shape of the firm growth distribution based on a model of proportional growth at the level of both the introduction of new products by firms and their size dynamics. We exploit the features(More)
We present a preferential attachment growth model to obtain the distribution P (K) of number of units K in the classes which may represent business firms or other socioeconomic entities. We found that P (K) is described in its central part by a power law with an exponent ϕ = 2+b/(1 − b) which depends on the probability of entry of new classes, b. In a(More)
The relationship between the size and the variance of firm growth rates is known to follow an approximate power-law behavior sigma(S) approximately S(-beta(S)) where S is the firm size and beta(S) approximately 0.2 is an exponent that weakly depends on S. Here, we show how a model of proportional growth, which treats firms as classes composed of various(More)