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gLOCAL Evaluation Week is a global knowledge-sharing week focused on monitoring and evaluation (M&E). According to the main text, the 2026 event will take place from June 1 to 5 and will include more than 300 online and in-person activities under the theme “Evaluation, Evidence, and Trust in the Age of AI.” Rather than a traditional single-course platform, it is more like an open learning and exchange network jointly participated in by institutions around the world.
The event focuses on topics such as artificial intelligence, digitalization, demand for evidence, evaluation workflows, capacity building, and the M&E ecosystem. Participants can browse the agenda and register for activities that interest them. The website also provides concept notes, working papers, blog posts, and recordings, summaries, or PPTs from some past events, though the availability of these materials depends on whether each event organizer uploads them.
At the institutional level, gLOCAL is convened and supported by the Global Evaluation Initiative (GEI). The main text states that GEI is hosted by the World Bank and managed by the Independent Evaluation Group of the World Bank Group; CLEARs, as GEI implementing partners, continue to play a role in regional coordination and event organization support. This gives it strong credibility in the fields of international development, public policy evaluation, and building government evidence systems.
The events are clearly free and open to everyone, and participants may attend as many sessions as they wish. It is worth noting that the gLOCAL organizing team does not issue participation certificates centrally; if a certificate is needed, participants must contact the specific event host. Therefore, if a user’s main goal is to obtain a certificate, they should confirm this separately before registering for a specific session.
Its advantages are its low barrier to entry, forward-looking themes, broad global coverage, and ability to connect international organizations, governments, academia, VOPEs, students, and other groups. It is especially valuable for learners who want to understand how AI is affecting evaluation and the use of evidence. The drawbacks are that the events are dispersed, and the learning path is less clear than that of a structured course; the quality, language, availability of materials, and certificate policies vary across different activities.
It is suitable for M&E practitioners, public policy and international development researchers, government or NGO project staff, evaluation commissioners, students, and anyone interested in the application of AI in evaluation. The main text does not provide information on access from mainland China, platform technology dependencies, or a language list, so its accessibility from China is considered unknown.
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