Studying 5.6 million biomedical science articles published over three decades, we reconcile conflicts in a longstanding interdisciplinary literature on scientists' life-cycle productivity by controlling for selective attrition and distinguishing between research quantity and quality. While research quality declines monotonically over the career, this decline is easily overlooked because higher "ability" authors have longer publishing careers. Our results have implications for broader questions of human capital accumulation over the career and federal research policies that shift funding to early-career researchers - while funding researchers at their most creative, these policies must be undertaken carefully because young researchers are less "able" on average.

Abstract This article presents an exploration of the usage and distribution of the 1-handshape classifier (Cl-1) and the 2-handshape classifier (Cl-2), both diachronically and synchronically, tracking classifier development in a detailed dataset of Nicaraguan individual homesigners and two groups of Nicaraguan Sign Language signers. Both phonological and semantic dimensions are analyzed in service of discerning what factors impact the choice and phonological production of the relevant classifiers. Phonologically we find that the distribution of Cl-1 and Cl-2 is quite different than would be expected were articulatory complexity the main motivating factor. We suggest also that this dataset is a microcosm of the system as a whole, and patterns of 1-handed and 2-handed signs vary across groups. Semantically, we find that (1) classifier use is more semantically restricted among individual homesigners. (2) As classifiers become more semantically frequent and flexible in the earliest cohort of Nicaraguan signers, constraints on production emerge. (3) Vertical transmission of those classifiers and constraints leads to more flexible usage in subsequent cohorts.

Studying 5.6 million biomedical science articles published over three decades, we reconcile conflicts in a long-standing interdisciplinary literature on scientists' life-cycle productivity by controlling for selective attrition and distinguishing between research quantity and quality. While research quality declines monotonically over the career, this decline is easily overlooked because higher ability authors have longer publishing careers. Our results have implications for broader questions of human capital accumulation over the career and federal research policies that shift funding to early-career researchers-while funding researchers at their most creative, these policies must be undertaken carefully because young researchers are less able on average.

Employment in STEM occupations suffered smaller peak-to-trough percentage declines than non-STEM occupations during the Great Recession and COVID-19 recession, suggesting a relative resiliency of STEM employment.We exploit the sudden peak-to-trough declines in STEM and non-STEM employment during the COVID-19 recession to measure STEM recession-resiliency, decomposing our difference-in-differences estimate into parts explained by various sources.We find that STEM knowledge importance on the job explains the greatest share of STEM employment resiliency, and that workers in non-STEM occupations who nonetheless use STEM knowledge experienced better employment outcomes.STEM employment resiliency may explain the mild effects of COVID-19 on innovative activity.

Countries, research institutions, and scholars are interested in identifying and promoting high-impact and transformative scientific research. This paper presents a novel set of text-and citation-based metrics that can be used to identify high-impact and transformative works. The 11 metrics can be grouped into seven types: Radical-Generative, Radical-Destructive, Risky, Multidisciplinary, Wide Impact, Growing Impact, and Impact (overall). The metrics are exemplified, validated, and compared using a set of 10,778,696 MEDLINE articles matched to the Science Citation Index Expanded (TM). Articles are grouped into six 5-year periods (spanning 1983-2012) using publication year and into 6,159 fields constructed using comparable MeSH terms, with which each article is tagged. The analysis is conducted at the level of a field-period pair, of which 15,051 have articles and are used in this study. A factor analysis shows that transformativeness and impact are positively related (rho = .402), but represent distinct phenomena. Looking at the subcomponents of transformativeness, there is no evidence that transformative work is adopted slowly or that the generation of important new concepts coincides with the obsolescence of existing concepts. We also find that the generation of important new concepts and highly cited work is more risky. Finally, supporting the validity of our metrics, we show that work that draws on a wider range of research fields is used more widely.