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Write a Qualitative Research Method Dataset

Write a Qualitative Research Method Dataset

Have you collected qualitative data in the social sciences? Are you interested in helping inexperienced researchers and students to learn about data analysis and interpretation? SAGE is looking for researchers to write short pedagogically focused, practical guides on how to conduct qualitative analysis: SAGE Research Methods Datasets.

What are SAGE Research Methods Datasets?

SAGE Research Methods Datasets are a new tool used in the teaching and learning of social science research methods in more than 160 institutions around the world. Each dataset is peer-reviewed and they present a practical guide to data analysis accompanied by real data for the reader to practice on. They are:

  • Short and accessible guides to specific research methods or techniques accompanied by real data used as an illustrative example.
  • Pedagogically focused to help students learn and practice their research methods.
  • Introductory in tone: explanatory and jargon-free.
  • Engaging: using examples and writing devices that reach out to the student reader and make research feel relevant, meaningful and useful.

Resources for Authors

Given that datasets is a very new style of writing, the following resources are available to authors considering writing a research methods dataset. Clicking on the links below will automatically download the Word documents needed to prepare a dataset for consideration. 

Frequently Asked Questions  Contributor Guidelines   Submission Template 

To take a look at previously published case studies, we recommend starting a 30-day free trial of the collection.

How to Get Involved 

  • To register your interest and set a submission deadline, please e-mail the following information to
    • Your name and institutional affiliation
    • Names of any co-authors, if applicable
    • Type of data you would provide (e.g. survey data, interview transcript, photographs etc.)
    • Method of analysis to be demonstrated (e.g. difference of means t-test, content analysis etc.)