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24 -May -2017
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WP7 - Researchers Mobility and Social Impact PDF Print E-mail

Description of results

WP Lead: Fundazione Roselli

The original goals of Workpackage 7 were to support the development of the SISOB project’s methodology by providing empirical investigations into the relationship between researchers’ mobility, research activities and social impact. The case study wanted to focus on the effects of on the performance of research activities measured according to several dimensions of social impact. It aimed to implement the methodologies developed in WP2 to WP6 to assess how researchers’ mobility affects research performance and impact.

WP7 further aimed to produce statistical indicators about the relation between mobility and research productivity and career development. The objective was to find objective patterns based on mobility and to identify "best practices" for the evolution of scientific communities.


These objectives were achieved through close interaction between the different work packages:


  • WP2
  • WP3 and WP6: Processes developed in WP 3 and 6 were tested to evaluate their feasibility for data collection.
  • WP4 : Indicators developed in WP4 were used to measure mobility and impact. They enabled us to measure the effect of mobility on different performance measures and helped increase our understanding of the link between mobility and performance.
  • WP5: Network indicators developed  were used to investigate thematic links. Visualisations  were used to visualise subject trajectories based on these networks. These help our understanding of disciplinary development and to comprehend the complexity of the process.


Elements of the conceptual model

The social impact of science depends on a broad range of factors, some linked to the way  scientific  knowledge  is  produced,  some  to  the  way  it  is  distributed  to  actors outside  the  science  production  system,  and  some  to  the  way  it  is  received,  applied, exploited  and  consumed.  All  involve  social  relationships  and  flows  of  information among  actors  (individuals,  institutions)  working  in  different  contexts  and  settings. Researcher mobility facilitates the flow of information and network building and as a consequence may improve the performance of scientific research. The mobility case study used elements of the SISOB conceptual model by looking at researchers as key actors in the science process

As a way to adopt the conceptual model to the requirements of WP7 one of the primary achievements is the development of a framework for the analysis of researcher mobility. We conceptualised mobility in a life course perspective that accounts for mobility events throughout a researcher’s career.  This approach has the advantage of observing more mobility events and thus allows drawing a broader picture of different patterns of past and current mobility. On the other hand, this approach also requires us to consider a larger number of groups in terms of mobility types and age cohorts.

Methods and Tools

Data

Methodology for data collection (D7.1) and its implementation
In collaboration with WP6 we developed a methodology to collect data for life-course analysis. The methodology implemented is based on a Web Crawling Process plus data extraction based in natural languague procesing. Departing from a general web search approximation, with inputs on basic information on the researchers and their current institutional affiliation, career data are gathered with the Crawler and then processed by a set of computational tools based on natural languague processing implemented based on the GATE tool. While the first one is concentrated in collect basic information like personal sites, current valid emails and CVs, the second is centred on detecting, organising and analysing several categories of the automatically collected CVs.

Methods

1. Econometric Framework for analysing effect on productivity (D7.1)

A third result of WP7 is the development of an econometric framework for the analysis of researcher mobility. Figure 3 represent the cycle between researcher's mobility and productivity, as well as the feedback relation that exists. Due to this feedback loop it is necessary to consider reverse causality issues.

We therefore need to discuss the motivations and expectations associated with each moves and make predictions on expected effects. To summarise our discussions in D7.1 and D7.2, we only expect a positive effect of mobility on performance if it involves a move to a better ranked institution and only after a short period of adjustment during which we expect a negative effect.

2. Series of new indicators

In collaboration with WP4 we developed a series of new indicators to be tested and used in WP7. The main variable of interest is research or research performance. The general performance of researchers is conceptualized in terms of publication productivity. We hypothesised that mobility affects the number and quality of publications of researchers as well as of institutions and regions. In this sense, we developed a set of new indicators:

a) Mobility (D7.1 / D4.2): On the vertical dimension we consider mobility along ranked systems or hierarchies of positions and locations. WP4.2 describes the vertical directional mobility path as (strict) monotonic paths, a continuously ascending or descending career, and non-monotonic paths, characteristic of more diverse trajectories, that exhibit a mixture of upward and downward steps.

b) Ranking (D7.2 / D4.2): In the Mobility Case Study it is of interest to rank institutions according to capital availability (resources and peers). Quality weighted publications per institution and field could provide such a measure and a (system of) time-variant ranking(s) was constructed providing means for registering significant career steps (through e.g. derived threshold values or scales for each ranking).

c) Thematic Mobility (D7.3 / D4.3 / D4.4): We applied the most recent toolbox of science mapping, partially developed through our own experience, via which both a research profile and its evolution can be thoroughly analysed and visualized. A measure originally proposed to account for the degree of multidisciplinarity was re-interpreted as indicating the degree of thematic mobility, through accumulation and through dynamic shift.

Results

First results of mixed effect of mobility on performance (D7.2)
Using a variety of indicators, data sources and models, we measured the effect of mobility on performance in four studies undertaken during the project. The results suggest generally that mobility is positively associated to scientific performance. However, this positive effect only follows after a period of adjustment during which we may observe a negative relationship. Further, the positive effect of a mobility event may not be lasting but disappear with time. The different studies show that the effects depend not only on the type of mobility considered, but also on the measure for scientific performance.  Further, the analysis may return different results depending on whether mobile researchers are compared to immobile researchers or to their own pre-mobility performance. Figure 4 gives evidence for this.


Geographic Mobility, source D7.2

Analysis
Time-Scale
Method
Performance Variable
Mobility Variable
Effect on Performance
Ex.1 The Mover's Advantage
2009
OLS
Impact Factor
returnee
+
foreign-born
+
visit abroad
-
nbregCitations  years
returnee
+
foreign-born
+
visit abroad
0
job abroad (returnees)
0
Ex.2 Mobile Scientists and International Networks
2009
Probit
international co-author
returnee
+
foreign-born+
Phd incoming
-
network > 4 countries
returnee+
foreign-born+
Phd incoming-
OLS
Impact factor (international papers)
returnee+
foreign-born+
Phd incoming-
Ex.4 Appointment, Promotion and Mobility of Bioscience Researchers in Japan
1980- 2010
stcox
promotion assoc in t
visit abroad
+
promotion full prof in t
visit abroad0
poisson (Diff-in-Diff PSM)
years to promotion ass.
visit abroad-
visit US
-
visit other country
0
years to promotion full
visit abroad-
visit US-


Sector Mobility, source D7.2

Analysis
Time-scale
Method
Perfomance Variable
Mobility Variable
Effect on Performance
Ex.3 Researchers' mobility and its impact on scientific productivity
1985-2005
nbreg
publication
mobility from industry
+
citations 5 years
mobility from industry+


Career Mobility, source D7.2

Analysis
Tme-scale
Method
Perfomance VariableMobility VariableEffect on Performance
Ex.1 The Mover's Advantage
2009
OLS
nbreg
Impact factor/citations
hindex origin country (foreign-born)+
hindex host country lower than origin+
hindex host country higher than origin+
Ex.3 Researchers' mobility and its impact on scientific productivity1985 - 2005
nbregpublication
upward mobility+
downward mobility-
citations 5 years
upward mobility
+
downward mobility
-


Thematic Mobility, source D7.3

Analysis
Tme-scaleMethod
Perfomance VariableMobility VariableEffect on Performance
Ex.5 Econometric analysis of individual thematic mobility1985 - 2007OLSPublicationThematic mobility level+

We used visualisations developed in D5.3 to graphically represent thematic trajectory paths based on thematic mobility indicators. In Figure 5 the metaphor shows different trajectories for the case of Engineering in the UK for the years 1985 to 2007. Using the SiSOB trajectory metaphor, we can detect different trajectories that lead to interdisciplinary research.

Implications and future work

Implications of specific results

The Mobility case study provides interesting, original  evidence on mobility and challenges the commonly accepted policy view that mobility is beneficial and should be encouraged. Our results point to a complex interaction between mobility and productivity, which only in certain circumstances might results in a positive impact of the former on the latter. Mobility is far from beeing always beneficial for individual researchers, instead, mobility is associated with a short-term decrease in performance due to adjustment costs and mobility to lower ranked department seems to result in decreased performance in the mid term. Further research on the specificities of mobility, for example mobility associated with career progress, mobility to and from business, mobility to a foreign country, and the career period in which the mobility occurs is needed to properly assess the impact of mobility and inform policy, especially in Europe, to support possible alternative forms of mobility.  If our results are confirmed by future work, this would call for a rethinking of policies related to researcher mobility.

Contributions to work bench

We provided a methodology for the collection of curricular data and its meaningful analysis which is being added to the SISOB workbench. In collaboration with WP6 we developed tools for collecting and structuring information on scientific researchers from publicly available websites and scientists’ CVs.

Applications of methods

The structured outputs of the tool can either be used for econometric research or for data representation for policy analysis. The data collection methodology is applied to the case of UK scientists but can be used in any other country in which scientists have the CV in English.
We further applied indicators designed in WP4. The ranking indicator was used to study mobility between UK universities. The thematic mobility indicator was tested on a longitudinal simple of UK engineering academics. Both indicators will be further developed in future studies.

Deliverables

Deliverable D7.1 Report on the analysis of researchers' mobility and the effects of researchers' mobility on research

Deliverable D7.2 Report on the effects of researchers' mobility in terms of scientific productivity

Deliverable D7.3 Report on the in-depth analysis of the effects of researchers' mobility on the development of disciplinary fields