Many surveys include questions that are asked in an open-ended format. For such questions, respondents are not offered a discrete set of options from which to choose. Instead, respondents answer in their own words. To protect respondent privacy and to facilitate quantitative analysis, survey producers later coded these open-ended responses by sorting them into discrete categorical variables.
Many researchers are asking important questions about the coding of open-ended responses. Some questions pertain to the properties of coding schemes. Other questions pertain to the procedures by which such schemes are implemented (e.g., how many coders to use and how to evaluate inter-coder reliability). Other questions pertain to documentation. There are, for example, numerous cases in which scholars who want to have debates about how to interpret coded responses cannot because surveys today tend to offer incomplete or inconsistent documentation of the coding properties and procedures described above.
Leading survey organizations, including the American National Election Studies, the General Social Survey, the Panel Study of Income Dynamics, and the National Longitudinal Survey are now seeking advice from a broad spectrum of experts about how to improve open-ended coding practices. To this end, they are co-sponsoring a conference on Optimal Coding of Open-Ended Survey Data at the University of Michigan on December 4 and 5, 2008.
The purpose of this conference is to bring together experts on systematic analysis of qualitative data and survey researchers to discuss options for improving conventional coding procedures implemented in the survey research world. Speakers and participants will include leading scholars from large-scale surveys, coding staff members from major survey organizations and scholars who have published and thought extensively about optimal procedures for coding open-ended text.
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Funded by the National Science Foundation and cosponsored by the American National Election Studies, the General Social Survey, the Panel Study of Income Dynamics, and the National Longitudinal Survey.