Discoverers in scientific citation data

Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to the citation network setting, and show that there are authors who frequently cite recent papers that become highly-cited in the future; these authors are referred to as discoverers. We develop a method for early identification of highly-cited papers based on the early citations from discoverers. The results show that the identified discoverers have a consistent citing pattern over time, and the early citations from them can be used as a valuable indicator to predict the future citation counts of a paper. The discoverers themselves are potential future outstanding researchers as they receive more citations than average

The Discoverers, by Daniel J. Boorstin

Book review by Charles T. Eby. Boorstin, Daniel J. The Discoverers. New York: Random House, 1983

How nobel-prize breakthroughs in economics emerge and the field's influential empirical methods

What drives groundbreaking research in economics? Nobel-prize-winning work has had an important impact on public policies, but we still do not understand well what drives such breakthroughs. We collect data on all nobel-prize discoveries in economics to address this question. We find that major advances in the field of economics are brought about by methodological innovation: by developing new and improved research methods. We find that developing for example econometrics in 1933, randomised controlled trials in 1948 and new game theory methods in 1950 were essential to opening the new fields of corporate finance, experimental economics and information economics, respectively. We identify the development of new methods as the main mechanism driving new discoveries and research fields. Fostering this general mechanism (generating novel methods) holds the potential to greatly increase the rate at which we make new breakthroughs and fields. We also show that many of the main methods of economics – such as randomised controlled trials, natural experiments, regression discontinuity, instrumental variables and other statistical methods – had been developed and used in other fields like public health, before economists adopted them. This shift towards more powerful empirical methods in the field has important implications on developing new and better methods and adopting them from related fields to make new advances more rapidly

Discovery Is Never By Chance: Designing for (Un)Serendipity

Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by ‘association-hunting’ agents. We propose considering not only the inventor’s role in perceiving serendipity, but also how that inventor’s perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately

Research on Instructional Strategies to Improve Geoscience Learning in Different Settings and with Different Technologies

Geoscience instruction today is carried out in a range of settings and with variously situated and richly contextualized teaching modalities. However, the pace and the excitement of technological and methodological advances in education tend to outstrip the more deliberate progress of relevant educational research and assessment. Further, geoscience education receives less attention and support on a national scale than do biology, chemistry, and physics education. As a result, many recent influential studies which demonstrated the effectiveness of active learning in undergraduate STEM, include little or no data from geoscience education. In order to close these gaps and render future instructional strategies as effective as possible, (a) there must be better coordination among researchers and educators in our own professional community and with those in other STEM disciplines; (b) higher standards of evidence must be applied to research in many cases; and (c) certain barriers at the instructional level to full and effective implementation of best practices must still be overcome. In this theme chapter, five grand challenges related to these issues are identified and described to spur more effective, accessible, inclusive, relevant, and practical geoscience teaching and learning

Intellectual Capital and the Birth of U.S. Biotechnology Enterprises

We examine the relationship between the intellectual capital of scientists making frontier discoveries, the presence of great university bioscience programs, the presence of venture capital firms, other economic variables, and the founding of U.S. biotechnology enterprises during 1976-1989. Using a linked cross-section/time- series panel data set, we find that the timing and location of the birth of biotech enterprises is determined primarily by intellectual capital measures, particularly the local number of highly productive 'star' scientists actively publishing genetic sequence discoveries. Great universities are likely to grow and recruit star scientists, but their effect is separable from the universities. When the intellectual capital measures are included in our poisson regressions, the number of venture capital firms in an area reduces the probability of foundings. At least early in the process, star scientists appear to be the scarce, immobile factors of production. Our focus on intellectual capital is related to knowledge spillovers, but in this case 'natural excludability' permits capture of supranormal returns by scientists. Given this reward structure technology transfer was vigorous without any special intermediating structures. We believe biotechnology may be prototypical of the birth patterns in other innovative industries.

The relationship between students' views of the nature of science and their views of the nature of scientific measurement

The present study explores the relationship between students’ views on the nature of science (NOS) and their views of the nature of scientific measurement. A questionnaire with two-tier diagnostic multiple choice items on both the NOS and measurement was administered to 179 first year physics students with diverse school experiences. Students’ views on the NOS were classified into four ‘NOS profiles’ and views on measurement were classified according to either the point or set paradigms. The findings show that students with a NOS profile which is dominated by a belief that the laws of nature are to be discovered by scientists, are more likely to have a view of the nature of scientific measurement characterised by a belief in ‘true’ values. On the other hand, students who believe that scientific theories are inventions of scientists, constructed from observations which are then validated through further experimentation, are more likely to have a view of the nature of scientific measurement which is underpinned by the uncertain nature of scientific evidence. The implications for teaching scientific measurement at tertiary level are discussed