Category: Paper notes

Notes on papers I read this week (II)

This week I have been reading a bunch of work on foreign-born scientists. I have focused on the works by Paula Stephan and colleagues. Here is some of the stuff and notes for future me.

Levin, S.G., Stephan, P. (1999). Are the foreign born a source of strength for U.S. science? Science, 285(5431), 1213-1214.

Inflow of foreign talent started in the 1970. This has been increasing for both, those coming before and after their PhD. The question posed in this paper is the following do foreign scientists (understood as both, born and educated) contribute disproportionally to US science? The authors conclude that this is actually happening especially with foreign-educated scientists. They conclude that the US is benefiting from foreign investment although they are unable to capture to what extent this poses a threat to US born or educated scientists.

Levin, G.S., Stephan, P. (1991). Research productivity over the life cycle: Evidence for academic scientists. The American Economic Review, 81(1), 114-132

They combine bibliometric and survey data. The goal of the paper is to analyze if productivity is motivated by either of two factors: investment for future rewards or consumption and the satisfaction of pursuing scientific advancement. They find that productivity tends to decline with age even when controlling for other factors. They conclude that therefore, productivity is investment-motivated rather than consumption-motivated.

Stephan, P.E., Levin, S.G. (2001). Exceptional contributions to US science by foreign-born and foreign-educated. Population Research and Policy Review, 20(1-2), 59-79.

Seems to be the paper used as basis for their Science policy forum. The dataset and conclusions are the same. They reinforce that the US has benefited overall from the attraction of foreign talent. When focusing on countries of origin of foreign scientists who make an exceptional contribution to the US (measured by their citation impact in both publications and patents) come mainly from the United Kingdom and Germany. Other contributing countries are Austria, Canada, China and India. They indicate higher rates of foreign scientists in later age cohorts (younger scientists).

Stephan, P. E., & Levin, S. (2003). Foreign scholars in US science: Contributions and costs. Science and the University, 237.

This paper wraps-up the findings from their different studies, some reviewed already above. Especially interesting is their analysis on displacement from and within academ of US scientists due to the increasing number of foreign scientists. In this case they find that there is a displacement from academe, as foreigners seem to be more competitive. However, this displacement within academia, only takes place on temporary jobs and not on permanent positions.

Franzoni, C., Scellato, G., & Stephan, P. (2014). The mover’s advantage: The superior performance of migrant scientists. Economics Letters, 122(1), 89–93.

This paper aims at isolating the effect of moving on productivity of scientists. They are trying to unveil if it is the movement itself what makes migrant scientists outperform non-mobile scientists. They measure performance based on the quartile of publications according to their journal impact factor. They combine survey and bibliometric data. According to their findings migrant scientists consistently outperform non-mobile despite of previous international collaboration or despite time of migration (before or after their PhD). This means that not only investing on scientists trained abroad is good business even bringing them to the country and training them.

Cover photograph: Reverse brain drain at http://www.stack.com.ph/brain-gain-linkedin-shows-that-smart-filipinos-are-coming-home/

Notes on papers I read this week (I)

Cañibano, C. & Bozeman, B. Curriculum vitae method in science policy and research evaluation: the state-of-the-art. Research Evaluation, 18(2), 86-94

This paper reviews the use of CV analysis in science policy. The value of CVs lies in the fact that they serve as personal services advertisement and the fact that researchers are strongly encouraged to provide timely and accurate data. Until early 1990s CV analysis has been used anecdotally and as complementary. However, the Research Value Mapping programme developed by Bozeman and Rogers among others, has fostered its expansion as a solid methodology. Contrarily to other methodological approaches, CV analysis is characterized by being theory-driven. There are three main research topics in which this method has been applied: Career trajectories, mobility and mapping collective capacity. However, CV analysis is not free of many methodological limitations, namely: availability, heterogeneity, truncation, missing information, and coding inconsistency. They suggest solving part of this problems by complementing the data with other sources such as bibliometric data or survey data.

Dietz, J.S. & Bozeman, B. (2005). Academic careers, patents, and productivity: industry experience as scientific and technical human capital. Research Policy, 34(2), 349-367

This paper intends to analyze productivity differences based on career paths of scientists within industry, government and academia who have ended up in academia. The paper is framed within Bozeman’s STHC framework. They argue that most studies have focused until then either in industry or academia and few on the collaboration patterns between academia and industry, but always considering researchers as either academic or industry, instead of acknowledge the diversity of career patterns observed in their trajectories. One of the arguments made is that by favoring capacity (in this case seen as richness in career trajectories) one favors knowledge production. Hence their first hypothesis is that those with more diversified career patterns will be more productive and confront it to another hypothesis which states that scientist who always worked in academia will be more productive. While the former is based on social capital grounds (more ties, more connections, more productivity), the latter is based on job priorization and incentives, as publication is one of the main tasks of scientists. Two alternative hypotheses are also formulated: 1) early career experiences in academia will lead to more productivity, and 2) publishing before PhD will also warrant being more productive in the future. They observe that precocity and homogeneity in career patterns has a weak positive relation with productivity while years in industry and time of PhD. They compared productivity means between those groups who moved from industry to academia and viceversa, before and after the moving and observed increased productivity in movements. While the framing of the paper is really strong and inspiring, its results are not sufficiently convincing.

Interesting points:

  • Homogeny variable. They ‘quantify’ careers based on how distant they are from the norm based on the probability of a given trajectory being similar to the always academic one.
  • Education and traning precocity. Based on PhD year and whether they had academic experience soon in their career and if they published before PhD.

 

Cover photograph: Workers of the world, unite! at https://flic.kr/p/5znVpk