Xu Z.,Rovira i Virgili University |
Archambault E.,Science Metrix
Scientometrics | Year: 2015
During the last 30 years, the growth of the interpreting industry in China has been outstanding. Increasing economic and political collaboration has driven the demand for interpreters to bridge the linguistic and cultural divides that exist between China and the West. With the creation of master’s and bachelor’s degrees in interpreting and translation all over China, hundreds of graduates from various universities have since undertaken distinctly different career paths. Using an exhaustive corpus of Masters’ theses and a combination of logistic regression and Targeted Maximum Likelihood Estimation to establish causalities, this paper focuses on some of the structural determinants of graduate students’ career choices. The paper examines to what extent university affiliations, thesis advisors, research methodology and thesis content influence the choice to pursue an academic career. The research reveals that graduating from a top university makes students less likely to become academics, and studying under a top advisor does not necessarily increase an individual’s chances of securing an academic post. By contrast, writers of empirical theses or ones that are about training are more likely to enter the academic sphere. © 2015 Akadémiai Kiadó, Budapest, Hungary
Mirshahvalad A.,Umea University |
Beauchesne O.H.,Science Metrix |
Archambault E.,Science Metrix |
Rosvall M.,Umea University
PLoS ONE | Year: 2013
Community detection helps us simplify the complex configuration of networks, but communities are reliable only if they are statistically significant. To detect statistically significant communities, a common approach is to resample the original network and analyze the communities. But resampling assumes independence between samples, while the components of a network are inherently dependent. Therefore, we must understand how breaking dependencies between resampled components affects the results of the significance analysis. Here we use scientific communication as a model system to analyze this effect. Our dataset includes citations among articles published in journals in the years 1984-2010. We compare parametric resampling of citations with non-parametric article resampling. While citation resampling breaks link dependencies, article resampling maintains such dependencies. We find that citation resampling underestimates the variance of link weights. Moreover, this underestimation explains most of the differences in the significance analysis of ranking and clustering. Therefore, when only link weights are available and article resampling is not an option, we suggest a simple parametric resampling scheme that generates link-weight variances close to the link-weight variances of article resampling. Nevertheless, when we highlight and summarize important structural changes in science, the more dependencies we can maintain in the resampling scheme, the earlier we can predict structural change. © 2013 Mirshahvalad et al.
Beaudet A.,Imperial College London |
Archambault E.,Science Metrix |
Campbell D.,Science Metrix
26th Electric Vehicle Symposium 2012, EVS 2012 | Year: 2012
This paper presents the results of a technometric analysis of battery patents. The results confirm the view that Japan and Korea lead the battery technology sector not only in manufacturing but also in R&D activity, which is measured using patent stocks as a proxy. We also found that the battery patent portfolios of these countries are younger than those of other countries, and that Japan and Korea are also more "specialized" in battery technology, i.e. they have in the past allocated a higher share of their total R&D efforts to batteries than other countries. A possible implication of these results is that Asia's competitive advantage in battery technology is likely to increase over time relative to North America and Europe. A ftirther implication is that Asian countries led by Japan and Korea stand to benefit the most from the trend toward powertrain electrification in the global automotive industry.