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Best practices for collaborative reflexive thematic analysis : news coverage of sexual violence in Canadian media / Tugçe Ellialti-Köse, Sami Falkenstein.

Sage Research Methods: Inclusive Research Methodologies Available online

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Format:
Book
Author/Creator:
Ellialti-Köse, Tugçe, author.
Falkenstein, Sami, author.
Language:
English
Subjects (All):
Sex crimes--Press coverage--Canada.
Sex crimes.
Qualitative research--Methodology.
Qualitative research.
Data sets.
Physical Description:
1 online resource : illustrations
Place of Publication:
London : SAGE Publications Ltd, 2026.
Summary:
As qualitative research continues to evolve, collaborations are increasingly valued for their ability to enhance scientific rigor and validity, while integrating diverse perspectives and fostering shared knowledge production. In this dataset, we offer a step-by-step guide to conducting a collaborative reflexive thematic analysis (RTA), a widely used qualitative method in social science research. Known for its theoretical and epistemological flexibility, RTA emphasizes researcher subjectivity, aiming to produce rich, nuanced, and insightful interpretations of qualitative data. Below we describe how we applied Braun and Clarke’s six-phase framework in our analysis of how sexual violence was represented in Canadian newspapers between 2017, the year that #MeToo went viral, and 2024. For each phase, we outline the key tasks we completed using Excel and NVivo, and describe how we engaged in reflexivity throughout, emphasizing the importance of extensive journaling and peer debriefing. Additionally, we provide personal insights and examples to illustrate the purpose of every step. We conclude each phase with additional quick tips to support readers’ research processes. Finally, we each offer our reflections—as a professor and a graduate student—on our experiences collaborating in this study. Overall, this dataset serves as a practical guide for students engaging in collaborative projects, offering guidance on how to apply RTA in a thoughtful, efficient, and inclusive way. This dataset file is accompanied by a teaching guide, a student guide and how-to guide.
Notes:
Description based on XML content.
ISBN:
9781036245092
OCLC:
1594889387
Publisher Number:
T301337

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