Guidelines for establishing reliability when coding narrative data

Syed, Moin; Nelson, Sarah C.

doi:10.1177/2167696815587648

Cited by 803Reliability and Agreement in MeasurementQualitative Research Methods and ApplicationsComputational and Text Analysis Methods

Guidelines for establishing reliability when coding narrative data

Syed, Moin, Nelson, Sarah C.·2015·Emerging Adulthood

DOI 10.1177/2167696815587648

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Abstract

The use of quantitative, qualitative, and mixed methods approaches has been foundational to research on emerging adulthood, yet there remain many unresolved methodological issues pertaining to how to handle qualitative data. The purpose of this article is to review best practices for coding and establishing reliability when working with narrative data. In doing so, we highlight how establishing reliability must be seen as an evolving process, rather than simply a focus on the end product. The review is divided into three broad sections. In the first section, we discuss relatively more quantitatively focused methods of coding and establishing reliability, whereas in the second section we discuss relatively more qualitatively focused methods. In the final section, we provide recommendations for researchers interested in coding narrative and other types of open-ended data. This article is intended to serve as an essential resource for researchers working on a variety of topics related to emerging adulthood and beyond.

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Trained raters allow multiple coders to demonstrate inter-rater reliability, which enhances results' internal and external validity.
“Chiefly, it allows multiple coders to demonstrate inter-rater reliability, which enhances results’ internal and external validity (Adler et al., 2017; Syed & Nelson, 2015).”
From Narrative identity in the psychosis spectrum: A systematic review and developmental model (2021) · cites this paper as Syed & Nelson, 2015

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Authors: Syed, M., & Nelson, S. C.
Affiliations: University of Minnesota (US)
Corresponding author: Syed, Moin
ORCID: Syed, Moin
Nelson, Sarah C.
Venue: Emerging Adulthood
Publisher: SAGE Publications
Published: 2015-05-26
Volume: 3
Issue: 6
Pages: 375-387
ISSN: 2167-6968 (ISSN-L)
2167-6984
DOI: 10.1177/2167696815587648
OpenAlex: W2232317411
Cited by: 801
References: 92
Citations by year: 2026: 63 · 2025: 83 · 2024: 106 · 2023: 89 · 2022: 117 · 2021: 126 · 2020: 96 · 2019: 62 · 2018: 28 · 2017: 23 · 2016: 7 · 2015: 1
FWCI: 17.94
Type: journal article
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Emerging Adulthood (publishedVersion)
OSF Preprints (OSF Preprints) (submittedVersion)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
Social Sciences › Education › Qualitative Research Methods and Applications
Social Sciences › General Social Sciences › Computational and Text Analysis Methods
Keywords: narrative data, coding reliability, qualitative data analysis, coding practices, mixed methods

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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Guidelines for establishing reliability when coding narrative data

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Integrity signals

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