Resources
Global Integrity, in collaboration with Making All Voices Count, has compiled material from the Learning to Make All Voices Count program.
In this program, they worked with six partners in five countries and supported their efforts to develop and apply an adaptive, learning-centred approach to strengthening subnational citizen engagement in their contexts. There is a focus on complexity-aware MEL as a crucial component of this approach.
This resource and the following information was contributed by Michael Moses.
Authors and their affiliation
- Michael Moses, Global Integrity
- Sue Soal, Independent Consultant
Key features
Key documents include:
Final Report:
Policy Briefs:
Case Stories:
Some of this material might be of interest to those exploring how MEL can be used to strengthen efforts pursue change in complex systems.
How have you used or intend on using this resource?
These resources were developed with a view towards generating useful guidance for practitioners interested in exploring how to support effective learning and adaptation in complex systems. They provide granular examples, and deeply evidenced lessons, on whether and how adaptive processes, including complexity-aware MEL, can support change processes in complex systems.
Why would you recommend it to other people?
The resources provide richly illustrated case stories of complexity-aware MEL in action, and explores whether/how MEL can inform real time efforts to learn and adapt in complex systems. They therefore provide guidance and lessons to those interested in pursuing systems change, including with respect to the role that MEL systems might play in such efforts, and do so in an easily intelligible, engaging way.
Sources
Citation for Final Synthesis Report:
Moses, M. (2017) Learning to Make All Voices Count: Lessons and reflections on localising the Open Government Partnership, Making All Voices Count Research Report, Brighton: IDS. https://www.globalintegrity.org/multi-stakeholder-governance-initiatives/learning-to-make-all-voices-count/