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Learn valuable insights for crafting qualitative social science proposals. Understand the unique strengths and limitations of qualitative methods, the importance of transparent data analysis, pitfalls of multi-method research, balancing tight proposals with room for new findings, transformative potential, and leveraging rejected proposals for resubmission.
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Six things I didn’t know about NSF review before I joined a panel Lessons for qualitative social science proposals
1. Qualitative research is respected on its own terms. • Understand what you are and are not able to do with the methods that you employ. • Not a representative sample, but… • Not able to test hypotheses (use research questions). • Define your terms (semi-structured interview, Q-Sort, NVivo, etc.) • Justify your choices.
2. Data analysis cannot be a black box. • Data analysis: Step between collecting information and final product. • Qualitative methods: content analysis, discourse analysis, narrative analysis… • Software doesn’t analyze your data, you do! • Give examples of how you will interpret information to answer research questions.
3. Multi-method research has strengths, but can backfire. • Kitchen sink problem. • Lack of expertise in all methods. • Make sure all research methods proposed are both appropriate and necessary.
4. There is a fine line between a tight proposal and one without room for new findings. • How will you know if you are wrong? • What might surprise you? • Include discussion of possible counter-intuitive findings.
5. Transformative potential can trump concerns about success. • Not necessary to be transformative. • Not necessary to call your research transformative (might backfire). • Will your research upend conventional wisdom, policy practices, or theory?
6. Reviewers often WANT to see rejected or unfunded proposals again (revised). • Revise and resubmit: “A better proposal would…” • Research already underway has better chance of funding.