Optimizing Grounded Theory for Policy Research

Grounded theory (GT) has become an influential methodology for research inquiry which involves the texts of human communication and language use as its primary empirical focus of data collection and analysis. However, influential models of GT have been most typically applied to the process of interp...

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Main Authors: Cameron Richards, Farrokh Farrokhnia
Format: Article
Language:English
Published: SAGE Publishing 2016-02-01
Series:International Journal of Qualitative Methods
Online Access:https://doi.org/10.1177/1609406915621380
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spelling doaj-d5b78f9aaeae4cadb3f054160d1b260e2020-11-25T03:18:22ZengSAGE PublishingInternational Journal of Qualitative Methods1609-40692016-02-011510.1177/160940691562138010.1177_1609406915621380Optimizing Grounded Theory for Policy ResearchCameron Richards0Farrokh Farrokhnia1 Faculty of Education, Southern Cross University, Gold Coast, Australia Perdana School of Policy Studies, University of Technology Malaysia, Kuala Lumpur, MalaysiaGrounded theory (GT) has become an influential methodology for research inquiry which involves the texts of human communication and language use as its primary empirical focus of data collection and analysis. However, influential models of GT have been most typically applied to the process of interpreting nonformal and especially “unstructured” texts such as conversations, interviews, and online communications. By contrast, policy researchers have the rather different challenge of interpreting the innate contradictions, diverse imperatives, and often conflicting perspectives which inform the meanings of policy positions as well as documents across different contexts. Building upon the interdisciplinary implications of recent constructivist models of the methodology, this article investigates how an optimizing “knowledge-building” approach represents an exemplary model for using GT for policy document research purposes. It does so in relation to the case study of a project focused on emergent as well as contextual dilemmas of analyzing World Trade Organization e-commerce policies.https://doi.org/10.1177/1609406915621380
collection DOAJ
language English
format Article
sources DOAJ
author Cameron Richards
Farrokh Farrokhnia
spellingShingle Cameron Richards
Farrokh Farrokhnia
Optimizing Grounded Theory for Policy Research
International Journal of Qualitative Methods
author_facet Cameron Richards
Farrokh Farrokhnia
author_sort Cameron Richards
title Optimizing Grounded Theory for Policy Research
title_short Optimizing Grounded Theory for Policy Research
title_full Optimizing Grounded Theory for Policy Research
title_fullStr Optimizing Grounded Theory for Policy Research
title_full_unstemmed Optimizing Grounded Theory for Policy Research
title_sort optimizing grounded theory for policy research
publisher SAGE Publishing
series International Journal of Qualitative Methods
issn 1609-4069
publishDate 2016-02-01
description Grounded theory (GT) has become an influential methodology for research inquiry which involves the texts of human communication and language use as its primary empirical focus of data collection and analysis. However, influential models of GT have been most typically applied to the process of interpreting nonformal and especially “unstructured” texts such as conversations, interviews, and online communications. By contrast, policy researchers have the rather different challenge of interpreting the innate contradictions, diverse imperatives, and often conflicting perspectives which inform the meanings of policy positions as well as documents across different contexts. Building upon the interdisciplinary implications of recent constructivist models of the methodology, this article investigates how an optimizing “knowledge-building” approach represents an exemplary model for using GT for policy document research purposes. It does so in relation to the case study of a project focused on emergent as well as contextual dilemmas of analyzing World Trade Organization e-commerce policies.
url https://doi.org/10.1177/1609406915621380
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