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Michael Kahn Research & Innovation Associates, Cape Town, South Africa

Measuring the Social Sciences Standing Committee on the Social Sciences European Science Foundation Bath, 21-23 October 2009. Michael Kahn Research & Innovation Associates, Cape Town, South Africa. This presentation. The task Issues Quantifying Social Science: the EU-27 Improving the data.

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Michael Kahn Research & Innovation Associates, Cape Town, South Africa

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  1. Measuring the Social Sciences Standing Committee on the Social SciencesEuropean Science FoundationBath, 21-23 October 2009 Michael Kahn Research & Innovation Associates, Cape Town, South Africa

  2. This presentation • The task • Issues • Quantifying Social Science: the EU-27 • Improving the data

  3. The task • Contribute to WSSR 2009/10: “Measure for measure: quantifying the social sciences” • Go beyond the data of the WSSR 1999 - OECD 29 countries; EU-15 • WSSR 2009/10: OECD 30; EU-27 + other large performers • Financials; equity; personnel inc. gender; graduate flows & outputs & scientific publications • Main sources: OECD, Eurostat, UNESCO Institute for Statistics. RICYT (Latin America); national orgs; commercial databases

  4. “Social Sciences in OECD” (Oba, WSSR 1999) Covers 29 OECD member states Sought to quantify scale of inputs; graduates; Frascati Manual R&D definition and collection guidelines SS R&D financials for 21 countries; personnel data for 19 – excludes large systems: FR, US, UK, KR, and smaller - CZ, GR, IT, LX, NZ, SL. Commentary on the practice of SS; notes ‘Data … often not very accessible to researchers”; identifies blurring of SS/H boundary as problem

  5. WSSR 1999: Social Sciences in the OECD

  6. Issues: What counts as R&D Frascati 6th Ed 2002: ‘creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications’ Recognizes increasing role of Services sector Basic, applied research, experimental development Related STAs excluded Clinical trials; software development … IN Much Social Science activity OUT

  7. Issues: Financials • Sectors: BUS, GOV, HE, NPO - boundary issues • In-house BERD; GOVERD, HERD, NPOERD  GERD • Expenditure = capex + labour + other current • Sources of Funds • GERD: GDP • Expenditure by region; Regional ERD: Gross geographic product • Expenditure by accounting category; type; region; Field of Science; Socio-economic Objective

  8. ESF OECD definition agree; UNESCO education =outside; national bodies ‘do it my way’

  9. Personnel Headcount (HC) Full-time equivalent (FTE) Technicians; Other staff  labour cost Qualifications; Gender, Age, Nationality Doctoral students; ; Research Assistants IN Research Masters students OUT

  10. Other items • FTE by gender per Field of Science (FoS) • Research collaboration • Expenditure by priority area • Mobility data

  11. Problems • BERD difficult to compute  purposive survey • SS often excluded from BERD: “designed out” • But SS important in Services; >60% GDP • R&D in Services 40% BERD in AU; 25% UK • And R&D tax incentives may exclude SS • HERD and GOVERD by census; • NPO purposive – boundaries porous • FTE “must” be < 100%; estimation; diary studies • Doctoral, postdocs, research assistants – FTE?

  12. The Story: Researchers in SS 25: Czech Republic, Hungary, Poland, Romania, Russian Federation, the Slovak Republic, Slovenia, Turkey, Mexico, Chinese Taipei, Japan, Singapore, Austria, Belgium, Canada, Denmark, Germany, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, and Sweden 17 EU; 20 OECD Of top five R&D performing nations, only DE and JP have official data

  13. OECD, 2006 (MSTI 2009/1) Little change since 1999

  14. The need for estimates EU 17 have SS FTE for HE; ESF 19 Large performers missing: FR, UK, also FI. Newcomers more compliant?

  15. Comments on the data What is underlying purpose of data collection? FTE R is critical; costly; estimates contested Student data more robust Propensity to publish varies by discipline FTE SS ≈0.25 total, but articles ≈ 0.12 total Publications counts biased by English language & location of publishing houses c.f. UK SS FTE vs UK share of SSCI; similar for SCOPUS Collate & compare ISI, SCOPUS (inc ERIH), Ulrich, Scielo Book publications and other artefacts: how to assess and track?

  16. Improving the next data set • Relationship with Science Policy. What data is required? What will be done with the data? Can Eurostat, OECD, UIS assist? Is FTE by Field of Science possible/necessary? If YES ….. • Implement a Project: “Social Science in the European Research Area” • Data requirement specification (DRS); define project scope • Examine Eurostat, OECD, UIS data; if data good  30/50 FTE • If available data falls short of expectation invoke direct collection through National Statistical Agencies/ designated parties  60/100 FTE • Later phase: online database with query functions; major updates at 5 year intervals

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