Language as a Factor in the Quality of Demographic Data and Translation Issues in the Management of Surveys

  • Jacob S. Siegel
Chapter

Abstract

Language in censuses and surveys is a special form of communication, requiring a degree of literacy and linguistic sophistication on the part of the respondent to understand the questions and respond appropriately to them. As sources of data secured from many persons with limited proficiency in the national language and as sources of data on language use and literacy, the products of censuses and surveys are imperfect. The survey process must be structured so as to encourage cooperation, but cooperation cannot always be achieved. The resulting errors range from incomplete coverage of the population, called an undercount, to failure to report on items on the questionnaire, called nonresponse error, and responding erroneously to items on the questionnaire, called item-response error. Unless adequate adjustments are made for these errors, the results will probably be biased. This chapter will be concerned mainly with the problems attendant to the enumeration in censuses and surveys of persons with limited proficiency in English and the methods used to overcome, reduce, and manage such problems, particularly the use of translation devices.

References and Suggested Readings

Effect of Language Proficiency on Quality of Source Data

  1. Bardage, C., Plujim, S. M. F., Pedersen, N. L., Deeg, D. J. H., et al. (2005). Self-rated health among older adults. A cross-national comparison. European Journal of Aging, 2, 149–158.CrossRefGoogle Scholar
  2. Carter, G. R. III, Schoua-Glusberg, A., & Sha, M. (2009). Language, culture, and respondent knowledge: Findings from the cognitive test of the Spanish translation of the American Housing Survey. AAPOR, May 14–17, 2009, pp. 5925–5939.Google Scholar
  3. Conrad, F. G., & Schnober, M. F. (2000). Clarifying question meaning in a household telephone survey. Public Opinion Quarterly, 64, 1–28.CrossRefGoogle Scholar
  4. Fitzgerald, R., & Jowell, R. (2010). Measurement equivalence in comparative surveys: The European social survey (ESS) from design to implementation and beyond. In J. A. Harkness, M. Braun, B. Edwards, T. P. Johnson, et al. (Eds.), Survey methods in multinational, multiregional and multicultural contexts (pp. 485–496). Hoboken: Wiley.CrossRefGoogle Scholar
  5. Griffin, D. (2006). Requests for alternative language questionnaires. In American Community Survey discussion papers. Washington, DC: U.S.Census Bureau.Google Scholar
  6. Griffin, D., & Broadwater, J. (2005). American Community Survey noninterview rates due to language barriers. Paper presented at the meetings of the Census Advisory Committee on the African-American Population, the American Indian and Alaska Native Populations, the Asian Population, the Hispanic Population, and the Native Hawaiian and Other Pacific Islander Population on April 25–27, 2015.Google Scholar
  7. Jabine, T., Straf, M., Tanur, J., & Tourangeau, R. (Eds.). (1984). Cognitive aspects of survey methodology: Building a bridge between disciplines. Washington, DC: National Academy Press.Google Scholar
  8. Kim, J., & Zapata, J. (2012). 2010 language program assessment report. 2010 census planning memorandum No. 204. Washington, DC: U.S. Census Bureau.Google Scholar
  9. Platt, J. (2002). The history of the interview. In J. F. Gubrium & J. A. Holstein (Eds.), Handbook of interview research. London: Sage.Google Scholar
  10. Sirken, M. G., Herrmann, D. J., Schechter, S., Schwartz, N., et al. (Eds.). (1999). Cognition and survey research. New York: Wiley.Google Scholar

Translation and Interpretation

  1. Arnold, F., & Reines, K. I. (1990). Strategies for translating DHS questionnaires. In DHS technical notes, DHS. Washington, DC: ICF International.Google Scholar
  2. Baker, M. (2014). The changing landscape of translating and interpreting studies. In S. Bermann & C. Porter (Eds.), A companion to translation studies (pp. 15–27). New York: Wiley.Google Scholar
  3. Cronin, M. (2013). Translation in a digital age. London: Routledge (Taylor and Francis).Google Scholar
  4. Doer, L. (2005). Lost in translation: Data quality and interpreters in multilingual research: Towards an interpreting methodology. Paper presented at the Annual Conference of the American Association for Public Opinion Research, Miami, FL, May12–15, 2005.Google Scholar
  5. Guérin-Pace, F., & Blum, A. (2000). The comparative illusion: The international adult survey. Population (English Selection), 12(2000), 215–246.Google Scholar
  6. Harkness, J. A. (2003). Questionnaire translation. In J. A. Harkness, F. J. R. van de Vivjer, & P. P. Mohler (Eds.), Cross-cultural survey methods. Hoboken: Wiley.Google Scholar
  7. Harkness, J. A., & Shoua-Glusberg, A. (1998). Questionnaires in translation (pp. 87–126). ZUMA-Nachrichten Spezial, Jsnuary 1998.Google Scholar
  8. Harkness, J. A., van de Vivjer, F. J. R., & Mohler, P. P. (Eds.). (2003). Cross-cultural survey methods. Hoboken: Wiley.Google Scholar
  9. Harkness, J. A., Edwards, B., Hansen, S. E., Miller, D. R., & Vilar, A. (2010a). Designing questionnaires for multipopulation research. In J. A. Harkness, M. Braun, B. Edwards, T. P. Johnson, et al. (Eds.), Survey methods in multinational, multiregional and multicultural contexts (pp. 53–58). Hoboken: Wiley.CrossRefGoogle Scholar
  10. Harkness, J. A., Vilar, A., & Edwards, E. (2010b). Translation, adaptation and design. In J. A. Harkness, M. Braun, B. Edwards, T. P. Johnson, et al. (Eds.), Survey methods in multinational, multiregional and multicultural contexts (pp. 117–140). Hoboken, Wiley.Google Scholar
  11. Kirsch, I. (2001). The international adult literacy survey (IALS): Understanding what was measured. Princeton: Educational Testing Service.Google Scholar
  12. McGovern, P. D. (2004). A quality assessment of data collected in the American community survey for households with low English proficiency. Washington, DC: U.S. Census Bureau.Google Scholar
  13. Palosuo, H. (2000). How good is ‘normal’ health? An exercise in Russian-Finnish comparative survey methodology. Idäntutkimus—The Finnish Review of East European Studies, 7, 41–70.Google Scholar
  14. Pan, Y., & de la Puente, M. (2005). Census Bureau guideline for the translation of data collection instruments and supporting materials: Documentation on how the guideline was developed. In Statistical Research Division, Research Report Series (Survey methodology #2005–6). Washington, DC: U.S. Census Bureau. www.census.gov/srd/www/byname.html#1panyuling
  15. Pan, Y., & Lubkemann, S. (2014). Standardization and meaning in the survey of linguistically diversified populations: Insights from the ethnographic observation of linguistic minorities in 2010 census interviews. In R. Tourangeau, N. Bates, B. Edwards, T. P. Johnson, & K. M. Wolter (Eds.), Hard-to-survey populations. Cambridge: Cambridge University Press.Google Scholar
  16. Pan, Y., Sha, M., Park, H., & Schoua-Glusberg, A. (2008). 2010 census language program: Pretesting of census 2010 questionnaire in five languages. Prepared for U.S. Census Bureau, Project Number: 0209182.010.Google Scholar
  17. Pan, Y., Leeman, J., & Fond, M. (2013). Development of Census Bureau survey interpretation guidelines. Study Series (Survey Methodology #2013–27).Google Scholar
  18. Pan, Y., Leeman, J., Fond, M., & Goermann, P. (2014). Multilingual survey design and fielding: Research perspectives from the U.S. Census Bureau. U.S. Census Bureau, Center for Survey Measurement, Research Report Series (#2014-01).Google Scholar
  19. Poulain, M. (2014). Personal communications between M. Poulain and the author by e-mail May 16, 2014 and May 19, 2014.Google Scholar
  20. Poulain, M. (2015). Personal communication between M. Poulain and the author by e-mail on June 15, 2015.Google Scholar
  21. Poulain, M., Herm, A., & Pes, G. (2013). The blue zones: Areas of exceptional longevity around the world. Vienna Yearbook of Population Research, 11, 87–108.CrossRefGoogle Scholar
  22. Robine, J.-M., & Jagger, C. (2003). The Euro-Reves group 2 project. Creating a coherent set of indicators to monitor health across Europe. European Journal of Public Health, 13(3 Suppl), 6–14.Google Scholar
  23. Roseman, S. (2014). Anthropological idiolects and minoritizing translation in Galician ethnography. J. of Linguistic Anthropology, 24(1), 19–41.CrossRefGoogle Scholar
  24. Schaeffer, N. C., & Maynard, D. W. (2002). Occasions for intervention: Interactional resources for comprehension in standardized survey interviews. In D. W. Maynard, H. Houtkoop-Steenstra, N. C. Schaeffer, & J. van der Zouwen (Eds.), Standardization and tacit knowledge: Interaction and practice in the survey interview (pp. 261–280). New York: Wiley.Google Scholar
  25. Taviano, S. (2013). English as a lingua Franca. Special Issue of The Interpreter and Translator Trainer, 7(2), 2013.Google Scholar
  26. Tu, D. L., & Schwede, L. (2012). More than just overcoming language and literacy barriers: Non-response follow-up census enumeration of Chinese in San Francisco Chinatown. Paper presented at the International Conference on Methods for Surveying and Enumerating Hard-to- Reach Populations, New Orleans, October 31–November 3, 2012.Google Scholar
  27. U.S. Census Bureau. (2004). Census Bureau guideline: Language translation of data collection instruments and supporting materials. In Internal Census Bureau document. Washington, DC: U.S. Census Bureau.Google Scholar
  28. U.S. Census Bureau. (2010). Census program for evaluations and experiments. In 2010 Census Planning Memoranda, series #204. Washington, DC: U.S. Census Bureau.Google Scholar
  29. Vuorisalmi, M., Pietilä, I., Pohjolainen, P., & Jylhä, M. (2008). Comparison of self-rated health in older people of St. Petersburg, Russia, and Tampere, Finland: How sensitive is SRH to cross-cultural factors? European Journal of Aging, 5, 327–334.CrossRefGoogle Scholar
  30. Xiaodong W., & Xiuhong Y. (2002). Does what you speak matter? – Effect of Chinese dialect on fertility in China. Presented at the annual meeting of the Population Association of America, Atlanta, GA, May 8–11, 2002.Google Scholar

Machine Translation

  1. Forcada, M. L. (2010). Machine translation today. In Y. Gambier & L. van Doorslaer (Eds.), Handbook of translation studies (Vol. 1, pp. 215–223). Amsterdam: John Benjamins.CrossRefGoogle Scholar
  2. Google. (2017). A neural network for machine translation, at production scale. Google Research Blog. Accessed on Internet February 5, 2017.Google Scholar
  3. Hutchins, J. (2007). Machine translation: Problems and issues. Panel at Conference on December 13, 2007. Accessed on internet July 25, 2016 at www.hutchinsweb.me.uk/SUSU-2007-2ppt.pdf.
  4. Raley, R. (2003). Machine translation and global English. Yale Journal of Criticism, 16(2), 291–313.CrossRefGoogle Scholar
  5. Wikipedia. (2016). Machine translation. Internet article accessed 15 Dec 2016.Google Scholar
  6. Wikipedia. (2017). Google neural machine translation. Internet article accessed 5 Feb 2017.Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Jacob S. Siegel
    • 1
  1. 1.North BethesdaUSA

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