Abstract: Tenure is a cornerstone of the US academic system, yet its relationship to faculty research trajectories remains poorly understood. Conceptually, tenure systems may act as a selection mechanism, screening in high-output researchers; a dynamic incentive mechanism, encouraging high output prior to tenure but low output after tenure; and a creative search mechanism, encouraging tenured individuals to undertake high-risk work. Here, we integrate data from seven different sources to trace US tenure-line faculty and their research outputs at a remarkable scale and scope, covering over 12,000 researchers across 15 disciplines. Our analysis reveals that faculty publication rates typically increase sharply during the tenure track and peak just before obtaining tenure. Post-tenure trends, however, vary across disciplines: In lab-based fields, such as biology and chemistry, research output typically remains high post-tenure, whereas in non-lab-based fields, such as mathematics and sociology, research output typically declines substantially post-tenure. Turning to creative search, faculty increasingly produce novel, high-risk research after securing tenure. However, this shift toward novelty and risk-taking comes with a decline in impact, with post-tenure research yielding fewer highly cited papers. Comparing outcomes across common career ages but different tenure years or comparing research trajectories in tenure-based and non-tenure-based research settings underscores that breaks in the research trajectories are sharply tied to the individual’s tenure year. Overall, these findings provide an empirical basis for understanding the tenure system, individual research trajectories, and the shape of scientific output.

Abstract: While Carbon Dioxide Removal (CDR) solutions are considered essential to meet Paris Agreement objectives and curb climate change, their maturity and current ability to operate at scale are highly debated. The rapid development, deployment, and diffusion of such methods will likely require the coordination of science, technology, policy, and societal support. This article proposes a bibliometric approach to quantify the public use of early-stage research in CDR. Specifically, we employ generalized linear models to estimate the likelihood that scientific advances in eight different carbon removal solutions may induce (i) further production of scientific knowledge, (ii) technological innovation, and (iii) policy and media discussion. Our main result is that research in CDR is of significant social value. CDR research generates significant, positive, yet heterogeneous spillovers within science and from science to technology, policy, and media. In particular, advances in Direct Air Capture spur further research and tend to result in patentable technologies, while Blue Carbon and Bio-energy with Carbon Capture and Storage appear to gain relative momentum in the policy and public debate. Moreover, scientific production and collaborations cluster geographically by type of CDR, potentially affecting long-term carbon removal strategies. Overall, our results suggest the existence of coordination gaps between science, technology, policy, and public support.

Abstract: Scientific discovery is shaped by scientists’ choices and thus by their career patterns. The increasing knowledge required to work at the frontier of science makes it harder for an individual to embark on unexplored paths. Yet collaborations can reduce learning costs—albeit at the expense of increased coordination costs. In this article, we use data on the publication histories of a very large sample of physicists to measure the effects of knowledge and social relatedness on their diversification strategies. Using bipartite networks, we compute a measure of topic similarity and a measure of social proximity. We find that scientists’ strategies are not random, and that they are significantly affected by both. Knowledge relatedness across topics explains ~10% of logistic regression deviances and social relatedness as much as ~30% suggesting that science is an eminently social enterprise: when scientists move out of their core specialization, they do so through collaborations. Interestingly, we also find a significant negative interaction between knowledge and social relatedness, suggesting that the farther scientists move from their specialization, the more they rely on collaborations. Our results provide a starting point for broader quantitative analyses of scientific diversification strategies, which could also be extended to the domain of technological innovation—offering insights from a comparative and policy perspective.

Abstract: This paper empirically investigates how the inter-sectoral knowledge flows affect the international competitiveness of industries, once controlling for both cost and other technological factors. Using patent data on 14 manufacturing industries in 16 OECD countries over the period 1995–2009, we apply a network-based approach to capture the effect of industries' position in the flows of technical knowledge across industries, which we label inter-sectoral knowledge space. We find that (i) centrality and local clustering in the inter-sectoral knowledge space positively affect the export market shares of an industry, (ii) such two effects are rather redundant and (iii) national-level knowledge flows' impacts on international competitiveness are way stronger than international ones. Network measures of position in the knowledge space are found to be more relevant than standard technological indicators such as patent counts. Our results point to the importance of industries being well located in the stream of knowledge flows, rather than being innovative per se, and offer a novel yet robust proxy to measure technological factors affecting trade performances. In addition, we find evidence of geographical boundaries of knowledge flows.