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2 - Development of Empirical Multilingual Analytical Instruments

Published online by Cambridge University Press:  10 June 2019

By
Meng Ji
Edited by
Meng Ji  and
Michael Oakes
Meng Ji
Affiliation:
University of Sydney
Michael Oakes
Affiliation:
University of Wolverhampton
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Summary

This chapter introduces and illustrates the socially-oriented approach to empirical translation research which has been gaining momentum in recent years with the availability of large-scale multilingual and translational data bases and the advancement in corpus translation research methodologies. The proposed social turn aims to expand the current horizon of empirical translation research by developing and testing data-driven corpus analytical instruments to help address pressing social and research issues which have arisen from the increasing cross-cultural translation and communication of new social concepts, values and idea sets in more recent decades such as environmental protection and sustainable development. Discussions in this chapter draw upon the corpus-driven analysis of the translation, transmission and social communication of multilateral environmental agreements across a wide range of countries at different stages of economic and social development including developing and developed countries in Europe, East Asia, Asia-Pacific, Latin America and North America. The multilingual corpus analysis led to the development of a country-based ranking scheme to assess the level of multi-sectoral interaction within a country in terms of the communication of translated environmental management knowledge. This new ranking scheme was then compared with the widely endorsed global environmental performance index (EPI) and the strong alignment between the two ranking schemes verified the theoretical hypothesise that stronger multi-sectoral interaction at the national level can effectively enhance the overall environmental performance of a country.

Keywords

Socially-oriented empirical translation studiesenvironmental translation and communicationmulti-sectoral interactionmultilingual environmental terminology
Type
Chapter
Information
Advances in Empirical Translation Studies
Developing Translation Resources and Technologies
 , pp. 13 - 27
Publisher: Cambridge University Press
Print publication year: 2019

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References

Adger, W. Neil and Jordan, Andrew (eds.) (2009). Governing Sustainability. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Aron, Arthur, Coups, Elliot and Aron, Elaine N. (2013). Statistics for the Behavioral and Social Sciences. London and New York: Pearson Higher Education.Google Scholar
Bäckstrand, Karin (2006). Multi-stakeholder partnerships for sustainable development: Rethinking legitimacy, accountability and effectiveness. Environmental Policy and Governance 16(5), 290–306.Google Scholar
Benner, Thorsten, Reinicke, Wolfgang H. and Witte, Jan Martin (2004). Multisectoral networks in global governance: Towards a pluralistic system of accountability, Government and Opposition 39(2), 191–210.Google Scholar
Bowker, Lynne and Delsey, Tom (2016). Information science, terminology and translation studies. In Gambier, Yves and van Doorslaer, Luc (eds.), Border Crossings: Translation Studies and Other Disciplines. Benjamins Translations Library, vol. 126. Amsterdam: John Benjamins, 73–96.CrossRefGoogle Scholar
Briggs, David J. (2008). A framework for integrated environmental health impact assessment of systemic risks. Environmental Health 1(1), 61.Google Scholar
Chambers, Bradnee W. (2008). Interlinkages and the Effectiveness of Multilateral Environmental Agreements. New York: United Nations University Press.Google Scholar
Environmental Performance Index. (n.d.) https://epi.envirocenter.yale.edu.Google Scholar
Färw, R., Grosskopf, S. and Hernandez-Sancho, F. (2004). Environmental performance: An index number approach. Resource and Energy Economics 26(4), 343–352.Google Scholar
Hsu, A., Emerson, J., Levy, M., de Sherbinin, A., Johnson, I., Malik, O., Schwartz, J. and Jaitch, M. (2010). Environmental Performance Index. New Haven, CT: Yale Centre for Environmental Law and Policy, vol. 87.Google Scholar
Hsu, Angel and Zomer, Alisa (2016). Environmental Performance Index. Wiley StatsRef: Statistics Reference Online.Google Scholar
InforMEA (2017). Multilateral environmental agreements and international environmental law. InforMEA (web). https://informea.org/terms.Google Scholar
Interactive Terminology for Europe (Portuguese) (n.d.). (web) https://iate.europa.eu/homeGoogle Scholar
Johal, Rajiv (2009). Factiva: Gateway to business information. Journal of Business and Finance Librarianship (15) 1, 60–64.CrossRefGoogle Scholar
Johnson, Ian and Macphail, Alastair (2000). IATE-Inter-Agency Terminology Exchange: Development of a single central terminology database for the institutions and agencies of the European Union. In Workshop on Terminology Resources and Computation.Google Scholar
Kockaert, Hendrik J., and Steurs, Frieda (2015). Handbook of Terminology. Amsterdam: John Benjamins.Google Scholar
Lim, S., Vos, T. and Flaxman, A. D. et al. (2012). A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010, Lancet 380(9859), 2224–2260.CrossRefGoogle Scholar
Smith, Kirk R. and Ezzati, Majid (2005). How environmental health risks change with development: The epidemiologic and environmental risk transitions revisited. Annual Review of Environment and Resources 30, 291–333.CrossRefGoogle Scholar
UNTERM: The UN Terminology Database (n.d.) Welcome. The UN Terminology Database (web). https://cms.unov.org/UNTERM/portal/welcome.Google Scholar

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