The Global Learning for Adaptive Management initiative (GLAM)

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The Global Learning for Adaptive Management (GLAM) is an initiative funded by the United States Agency for International Development (USAID) and the Department for International Development (DFID). GLAM is envisioned as a globally networked learning alliance that aimed to actively identify, operationalise and promote rigorous evidence-based approaches to adaptive management.

GLAM aims to provide tailored guidance and practical support on adaptive management (AM) to practitioners and policymakers, generate high-quality evidence and learning about effective monitoring, evaluation and learning (MEL) for AM (MEL4AM), and act as a catalyst, champion and convenor to change thinking and practice.

GLAM key resources

GLAM has a legacy of research and a library focused on adaptive and MEL4AM work.

 

The adaptive management in international development library is available as an open source for the AM, MEL and thinking and working politically (TWP) communities and can be accessed here: https://adaptdev.info/lib. We would like to encourage the community to use this as a resource, and to keep updating it with relevant work. 

 

Additional resources such as working papers and briefing notes on topics such as M&E tools and approaches and adaptive rigour can be accessed on this page, or via the following links:

  1. USAID Wildlife Asia as a case study in adaptive rigour: monitoring, evaluation and learning for adaptive management
  2. Adapting data collection and utilisation to a Covid-19 reality
  3. Contribution analysis for adaptive management
  4. Outcome mapping: learning brief
  5. Supporting adaptive management: monitoring and evaluation tools and approaches
  6. Towards evidence-informed adaptive management: a roadmap for development and humanitarian organisations
  7. Monitoring and learning for country-level portfolio decision-making and adaptation
  8. Making adaptive rigour work: principles and practices for strengthening MEL for adaptive management

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