Knowledge that Transforms

We are very grateful to the editor of this virtual Special Section, Ben Martin, to open up the discussion on our proposal of partly random selection of publications (Osterloh and Frey, 2020). At first glance, our proposal might look crazy. Consider, however, the quote attributed to Albert Einstein: “if at first an idea is not absurd, then there is no hope for it”. Our reply takes up three considerations discussed by the commentators Oswald (2019), Wooding (2019) and Yaqub (2019): (1) additional aspects to our paper; (2) the discussion about how bad the Journal Impact Factor (JIF) is if applied to evaluate single articles; and (3) how to overcome JIF.

This paper analyses how differences in the industry composition of British local labour markets moderate the impact of foreign technological competition in manufacturing on domestic employment, both overall and across subsamples of workers with different skill levels (high, intermediate and low). To this scope, it exploits both variations across industries in the exposure to the introduction of new technologies, and information on how such industries are combined in shaping the industrial structure of each place. The analysis shows that places that specialise in industries undergoing substantial technological competition due to foreign innovation experience a reduction in total employment that is 4.5% larger than places less exposed based on their initial industry mix. This negative performance is mainly explained by a decrease in the employment opportunities for intermediate-skilled workers. Limited support is found for successful adaptation trajectories over time across British local labour markets.

The recruitment of foreign-trained scientists enhances US science through an expanded workforce but could also cause harm by displacing better connected domestically-trained scientists, thereby reducing localized knowledge spillovers. We develop a model in which a sufficient condition for the absence of overall harm is that foreign-trained scientists generate at least the same level of localized spillovers as the domestically-trained scientists they displace. To test this condition, we conduct a hypothetical experiment in which each foreign-trained displaces an appropriately matched domestically-trained scientist. Overall, we do not find evidence that foreign-trained scientists harm US science by crowding out better-connected domestically-trained scientists, measured by citations by the US scientific community to their publications.

We explore the contention that the seminal US National Academies consensus report, How People Learn (HPL), played a major role in bridging the flow of knowledge from Cognitive Science to Education. Our paper yielded four important results: First, HPL is, on a number of bibliometric measures, an unusually interdisciplinary work. Focusing on the fields of particular interest here, our citation analysis shows the Education, Cognitive Science, and Border field (e.g., Educational Psychology, Learning Sciences, and Learning Technology and Human-Computer Interaction) literatures all to have been major influences on it. Second, we found HPL to be unusually highly cited – and by publications from an unusually diverse set of disciplines. Beyond Education, Cognitive Science, and Border field publications, HPL was also relatively highly cited by publications in Medical/Health-related, Engineering, and other Discipline-Based Education Research fields. Third, undermining the claim that HPL served as a gateway to the Cognitive Science literature, we found Education articles citing HPL not to be more likely to have Cognitive Science as a major influence than are Education articles more generally, as indicated by their cited references. Finally, the Education publications that cited HPL were far more likely to refer to concepts in HPL that were already prevalent in the Education literature rather than to concepts from Cognitive Science. Conversely, the Cognitive Science publications that cited HPL were more apt to refer to concepts already in the Cognitive Science literature. Taken together, these results are a caution that, even for a highly regarded multidisciplinary work cited widely by publications from multiple disciplines, its direct influence could be largely disciplinary. Implications for the policy goals of fostering interdisciplinary research and the role of National Academies consensus reports are discussed.

The transfer of scientific material and data, which are scientific inputs, is fundamental to knowledge creation dynamics. This transfer is being controlled, more and more, by the use of Material Transfer Agreements (MTAs). Therefore, the effect of MTAs on the dynamic of knowledge creation is an important concern. The aim of this research is to characterise the restrictions imposed by MTAs, and their determinants. We consider MTA diversity based on a comprehensive analysis of the clauses included in 171 MTAs signed by two French universities. We show that the clauses included in MTAs depend on several factors such as kind of material involved, research field, patenting and collection of material. We find that the presence of an industry actor is not associated to more restrictions on publication and intellectual property. We propose a typology of MTAs corresponding to different transfer situations. We discuss the role of MTAs as collaborative tools and the influence of the legal, scientific, political and organisational context.

This technical note describes the results of a pilot approach to link administrative and survey data to better describe the richness and complexity of the research enterprise. In particular, we demonstrate how multiple funding channels can be studied by bringing together two disparate datasets: UMETRICS, which is based on university payroll and financial records, and the Survey of Earned Doctorates (SED), which is one of the most important US survey datasets about the doctoral workforce. We show how it is possible to link data on research funding and the doctorally qualified workforce to describe how many individuals are supported in different disciplines and by different agencies. We outline the potential for more work as the UMETRICS data expands to incorporate more linkages and more access is provided.