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Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions

The primary method by which social scientists describe public opinion about science and technology is to present frequencies from fixed response survey questions and to use multivariate statistical models to predict where different groups stand with regard to perceptions of risk and benefit. Such an...

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Detalles Bibliográficos
Autores principales: Stoneman, Paul, Sturgis, Patrick, Allum, Nick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4400270/
https://www.ncbi.nlm.nih.gov/pubmed/23825238
http://dx.doi.org/10.1177/0963662512441569
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author Stoneman, Paul
Sturgis, Patrick
Allum, Nick
author_facet Stoneman, Paul
Sturgis, Patrick
Allum, Nick
author_sort Stoneman, Paul
collection PubMed
description The primary method by which social scientists describe public opinion about science and technology is to present frequencies from fixed response survey questions and to use multivariate statistical models to predict where different groups stand with regard to perceptions of risk and benefit. Such an approach requires measures of individual preference which can be aligned numerically in an ordinal or, preferably, a continuous manner along an underlying evaluative dimension – generally the standard 5- or 7-point attitude question. The key concern motivating the present paper is that, due to the low salience and “difficult” nature of science for members of the general public, it may not be sensible to require respondents to choose from amongst a small and predefined set of evaluative response categories. Here, we pursue a different methodological approach: the analysis of textual responses to “open-ended” questions, in which respondents are asked to state, in their own words, what they understand by the term “DNA.” To this textual data we apply the statistical clustering procedures encoded in the Alceste software package to detect and classify underlying discourse and narrative structures. We then examine the extent to which the classifications, thus derived, can aid our understanding of how the public develop and use “everyday” images of, and talk about, biomedicine to structure their evaluations of emerging technologies.
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spelling pubmed-44002702015-04-17 Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions Stoneman, Paul Sturgis, Patrick Allum, Nick Public Underst Sci Articles The primary method by which social scientists describe public opinion about science and technology is to present frequencies from fixed response survey questions and to use multivariate statistical models to predict where different groups stand with regard to perceptions of risk and benefit. Such an approach requires measures of individual preference which can be aligned numerically in an ordinal or, preferably, a continuous manner along an underlying evaluative dimension – generally the standard 5- or 7-point attitude question. The key concern motivating the present paper is that, due to the low salience and “difficult” nature of science for members of the general public, it may not be sensible to require respondents to choose from amongst a small and predefined set of evaluative response categories. Here, we pursue a different methodological approach: the analysis of textual responses to “open-ended” questions, in which respondents are asked to state, in their own words, what they understand by the term “DNA.” To this textual data we apply the statistical clustering procedures encoded in the Alceste software package to detect and classify underlying discourse and narrative structures. We then examine the extent to which the classifications, thus derived, can aid our understanding of how the public develop and use “everyday” images of, and talk about, biomedicine to structure their evaluations of emerging technologies. SAGE Publications 2013-10 /pmc/articles/PMC4400270/ /pubmed/23825238 http://dx.doi.org/10.1177/0963662512441569 Text en © The Author(s) 2012 http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (http://www.uk.sagepub.com/aboutus/openaccess.htm).
spellingShingle Articles
Stoneman, Paul
Sturgis, Patrick
Allum, Nick
Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title_full Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title_fullStr Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title_full_unstemmed Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title_short Exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
title_sort exploring public discourses about emerging technologies through statistical clustering of open-ended survey questions
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4400270/
https://www.ncbi.nlm.nih.gov/pubmed/23825238
http://dx.doi.org/10.1177/0963662512441569
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