Self-coding: A method to assess semantic validity and bias when coding open-ended responses

Author:

Glazier Rebecca A.1,Boydstun Amber E.2ORCID,Feezell Jessica T.3

Affiliation:

1. University of Arkansas, Little Rock, USA

2. University of California, Davis, USA

3. University of New Mexico, USA

Abstract

Open-ended survey questions can provide researchers with nuanced and rich data, but content analysis is subject to misinterpretation and can introduce bias into subsequent analysis. We present a simple method to improve the semantic validity of a codebook and test for bias: a “self-coding” method where respondents first provide open-ended responses and then self-code those responses into categories. We demonstrated this method by comparing respondents’ self-coding to researcher-based coding using an established codebook. Our analysis showed significant disagreement between the codebook’s assigned categorizations of responses and respondents’ self-codes. Moreover, this technique uncovered instances where researcher-based coding disproportionately misrepresented the views of certain demographic groups. We propose using the self-coding method to iteratively improve codebooks, identify bad-faith respondents, and, perhaps, to replace researcher-based content analysis.

Publisher

SAGE Publications

Subject

Political Science and International Relations,Public Administration,Sociology and Political Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3