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An introduction to the themed section on ‘Using agent-based simulation for integrating qualitative and quantitative evidence’

This themed section of the International Journal of Social Research Methodology is devoted to discussing topics relevant for researchers working in projects involving “applied integrative research” through interdisciplinary or transdisciplinary projects that must use both qualitative and quantitative evidence.

Sukaina Bharwani / Published on 7 September 2022

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Citation

Antosz, P., Bharwani, S., Borit M., and Edmonds, B. (Eds.) (2022). An introduction to the themed section on 'Using agent-based simulation for integrating qualitative and quantitative evidence'. International Journal of Social Research Methodology, 25, 4. [Special issue on "Using agent-based simulation for integrating qualitative and quantitative evidence"]. https://doi.org/10.1080/13645579.2022.205265

Many approaches to understanding social phenomena use either only qualitative or only quantitative methods, and they have well-developed traditions concerning how to interpret their data or observations, and how to formulate their conclusions. However, this is a luxury unavailable to researchers that are part of interdisciplinary or transdisciplinary projects that aim to address practical problems within a complex context.

This themed section of the International Journal of Social Research Methodology is devoted to discussing topics relevant for researchers working in projects involving “applied integrative research” that involves multidisciplinary projects that must use both qualitative and quantitative evidence.

This themed section discusses the use of a formal but flexible approach: agent-based modelling. The editors argue that the methodological advances of the special section’s papers reveal that the approach is starting to mature in ways that facilitate the development and enrichment of both social science and of agent-based modelling itself.

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SEI author

Sukaina Bharwani

Senior Research Fellow and weADAPT Director

SEI Oxford

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SEI Oxford