Community Events

Second Workshop on Integrating Qualitative and Quantitative Evidence Using Social Simulation

The main aim of this workshop is to design collectively a strategy for structuring and developing the field, while stimulating research and technological advancements on this topic, providing a forum for the reporting and discussion of current approaches, and facilitating the development of subsequent collaborative work within the field and across fields. This is a 2-day event following-up the Lorentz Center workshop on “Integrating qualitative and quantitative evidence using social simulation”, April 2019 (

We invite all participants of the Lorentz workshop as well as other interested persons to join this follow-up workshop in Manchester; more news: The event will provide an opportunity for participants to:
- Present their work progresses, results or preliminary drafts of their work and receive feedback from other participants;
- Discuss the next steps i.e. continuing the planned work and/or initiating new work (e.g. grant application, focused publication, further workshops, journal special issue etc.).

Professor Alicia O’Cathain, University of Sheffield, UK
Title: “Various ways to integrate qualitative and quantitative data in mixed-methods research”

Manchester Metropolitan University Business School, All Saints Campus, Oxford Road, Manchester, M15 6BH, UK. More information:

There is no charge for the workshop, but advance registration is required via There is limited space available for 25 participants. Lunch & coffee will be provided free of charge.

- Deadline for registration: 24th October 2019
- Workshop itself: 9 AM 21st to 4 PM 22nd November 2019

- Melania Borit (Norway)
- Stephanie Dornschneider (Ireland)
- Bruce Edmonds (UK)
- Magnús Josefsson (Iceland)
- Sara Mehryar (UK)
- Nanda Wijermans (Sweden)

- Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK
- Norwegian College of Fisheries Science, UiT – The Arctic University of Norway, Tromsø, Norway
- ESSA SIG Using qualitative data to inform behavioral rules in ABM (


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