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A bibliometric approach to international scientific migration

A bibliometric approach to international scientific migration. Henk F. Moed , M’hamed Aisati , Andrew Plume and Gali Halevi Elsevier (Netherlands, UK, USA). Contents. Introduction : Migration and co-authorship The model Technical aspects Study countries and approaches

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A bibliometric approach to international scientific migration

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  1. A bibliometric approach to international scientific migration Henk F. Moed, M’hamedAisati, Andrew Plume and GaliHalevi Elsevier (Netherlands, UK, USA)

  2. Contents • Introduction: Migration and co-authorship • The model • Technicalaspects • Studycountries and approaches • Results: Global patterns • Publication (Scopus) vs. Survey (OECD) data • Accuracy / robustness of migration indicators • Conclusions

  3. Introduction:Migration vs. co-authorship

  4. Which country has these main collaborators? Brazil

  5. Which country has these main collaborators? Malaysia

  6. Which country has these main collaborators? Romania

  7. Which country has these main collaborators? SouthAfrica

  8. The model

  9. International migration vs. co-authorship

  10. The model - 1 Transients are deleted

  11. The Model – 2 First publi-cation 2nd p 3rd p 4th p Master degree PhD degree Start senior career Master PhD student Post doc Senior T B B B B B A A 1 A A B B B A A 2 B A A A A A A 3

  12. Technical aspects

  13. Technical aspects (in Scopus) • Author-affiliation linking • Author profiling

  14. Author-affiliation links Is Italian science declining? RESPOL, 2011 Cinzia Daraio (a) and Henk F. Moed (b) • Department of Management, Univ Bologna, Via U. Terracini, 28, 40131 Bologna, Italy • Centre for Science and Technology Studies (CWTS), Leiden University, The Netherlands

  15. Author-affiliation link records

  16. Author profiling in Scopus • Assigns to each author a unique number • Groups each author’s documents.... • ... based on similarity in affiliation, publication history, subject and co-authors • Aims at high precision ( lower recall) • New algorithm implemented in April 2011 • Author feedback system in place

  17. Categorization of authors in year T

  18. # Publishing authors per year and type (UK) TOTAL 2009 Cohort can be followed for one year only CONTINUANTS MOVERS Decline in # Newcomers TRANSIENTS NEWCOMERS

  19. Important distinction Use of author ID data to assess an individual vs Statistical analysis of patterns in large datasets X

  20. Study countries and approaches

  21. Countries with the largest increase in publication output during 2000-2010 (Scopus) > 10 %: Selected in current study

  22. Study countries (10 fast growers + 7 “big” countries)

  23. Two complementary approaches

  24. Results: Synchronousapproach

  25. Study set: % Young authors currently active in a study country Question: How many of them had stays abroad?

  26. Results: Asynchroneous approach

  27. Study set: authors starting their career in a study countryQuestion: How many moved abroad, how many returned?

  28. Study set: Young authors starting their career in a study countryQuestion: How many move abroad, how many return? Post Docsreturning to their home country? Post-Docsnotreturning to their country? OrPhDstudentsreturningafterattainingtheirPhD?

  29. Results: Publication (Scopus) data vs. Survey (OECD) data

  30. Inconsistencies in OECD data on # FTE Res? Differences in ratios between ITA and UK are almost a factor 2!

  31. Inconsistencies in data on # FTE Res? Differences in ratios between {ITA, NLD} and {DEU, UK} almost a factor 2

  32. Results: Migration vs. Co-authorship

  33. Migration and co-authorship patterns are statistically different N=694 Mean=0.75 STD=0.49 Skewness=1.59 Analyzed later

  34. Map of countries with Ratio migration/collaboration > 1.2

  35. Languagesimilarity drives migrationstrongerthanit drives co-authorship Politicaltensions affect migrationlessthanthey affect co-authorship

  36. Variation = 100*(max-min)/ (2*mean) Tentative error rates in migration indicators

  37. Conclusions • Migrationanalysisgeneratesnewinsightsinto the globalscientificnetwork • Relative indicators basedonlargenumbers areinsensitiveto errors in author profiles.

  38. Thank you for your attention

  39. PART II Robustness / accuracy of migration indicators

  40. Case study: Data sample analysed • 100 author-ids in chemistry randomly selected from Scopus • Search for other author-ids that relate to the same authors as those represented in the sample • Precision of the 100 author-ids themselves was not examined • Emphasis on recall rather than precision

  41. Author Countries CHN USA JPN DEU KOR Asian countries (China, Japan and Korea) are over-represented (n=34)

  42. Findings – 1 • 27% of the researchers did have additional author ID's • For the 27 % researchers that did have additional ID's, in total 51 additional author IDs were found • Half of the additional author IDs had 1 paper only; and 75 % at most 2

  43. 100 sample authors are linked with 151 author-ids # Author-ids with 1 paper = 2 x # authors with 1 paper # Author-ids with >=20 papers is 1.1 x # authors with >=20 papers # Author-ids with 2 papers = 1.6 x # authors with 2 paper

  44. Implications for the migration study

  45. Sensitivity Analysis: publication thresholds 1. ALL 2. P > 2 3. P > 3

  46. Sensitivity analysis: publ per year (Ppyr) thresholds 1. All 2. Ppyr < 7.0 3. Ppyr < 5.0

  47. No. Authors moving to a study country 2 3 1

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