COFFEE BREAK
Learn from the experts during a quick coffee break!
Join us for a Causal Pathways Coffee Break, in which experts share snippets of their Causal Pathways work and lessons learned. Grab your favorite warm drink and join us for a quick lesson!
Current offerings
Check this page regularly for updates on opportunities! Recordings for previous Coffee Breaks are available below.
11/12/26 @ 1:00pm ET
Full Circle Strategy: How Causal Thinking Shapes Decisions, Partnerships, and Practice
Materials
How can causal thinking shape strategy, partner selection, and measurement—even when the path from learning to action is not linear?
Hopelab participated in the very first Causal Pathways Initiative (CPI) Brain Trust, bringing a real strategic question into conversation with the CPI network. Among those at the table were Arianna Taboada, Director of Learning & Impact at Hopelab, and Dr. Kimberlin Butler, Founder & Chief Possibility Catalyst of The L.E.A.D. Agency—both members of the CPI network, with Kimberlin serving as a Network Co-Lead at the time.
Now, Arianna and Kimberlin are coming back together to examine what happened next.
Hopelab did not simply implement the Brain Trust recommendations. Instead, the experience influenced how the organization later developed a request for qualifications (RFQ), the process it used to identify a partner for its measurement work, and how it approached the resulting measurement plan. That work is now being implemented with the Center for Evaluation Innovation, creating what Arianna described as a “full circle” moment.
In this behind-the-scenes conversation, Arianna and Kimberlin will revisit where the journey began, explore what resonated with Hopelab and what evolved, and unpack how causal thinking surfaced in later strategic decisions, partner selection, and measurement. They will also consider what Hopelab’s experience can teach funders and practitioners about carrying learning forward when change does not unfold in a straight line. Register here.
Kimberlin Butler
The L.E.A.D. Agency
Arianna Taboada
Hopelab
12/1/26 @ 11:00am ET
Whose rigour? Designing causal pathways evaluations with the Inclusive Rigour Design Canvas
Materials
Causal pathways approaches ask us to take seriously how, why and for whom change happens. But the design choices we make early on shape the quality of the causal claims that we can make, and whose knowledge they rest on. These choices include which methods we (re)combine, who takes part in building and exploring causal explanations, and what counts as credible evidence.
In this Coffee Break, members of the Inclusive Rigour Co-Lab will introduce the Design Canvas and Workbook. Launched in June 2026 it is a practical resource for designing complexity-aware and participatory MEL. The Canvas brings together deliberation on the quality of evidence and the quality of participation, and grounding in shared values, to build an appropriate methodological bricolage, meaning the purposeful (re)combining of methods to answer causal questions. We’ll show how the Canvas can help evaluators and foundation learning staff make design choices explicit. These include choices about how to recombine causal methods such that experiences of system actors drive quality and meaning in causal explanations.
The session builds on our earlier conversations with the network on quality and rigour in causal pathways evaluation. We’ll share early use cases of the Canvas and our learning from these experiences. Bring your questions, and if you’re already using causal pathways methods, we’d love to hear where the Canvas might help or fall short. Register here.
Marina Apgar
Institute of Development
Studies
Helene Bradburn
Consultant
Past offerings
6/16/26 @ 11:00am ET
How robust are your causal pathways?
Materials
All evaluators, at some point, have to consider a mass of information from different sources about what might have contributed to an outcome and reach a conclusion about what did contribute to the outcome, and along which pathways. Now that AI can gather thousands of causal claims from text, making these decisions rigorously is particularly challenging.
This Coffee Break is about how to build rigour in an AI-assisted causal mapping workflow: how you interrogate the mass of evidence that something influences an outcome along a pathway, how to compare it with alternative explanations, how you handle weak or doubtful claims, and how you make the kind of evaluative judgements that you really don't want to leave to an AI.
Steve Powell and Gabriele Caldas (Causal Map Ltd) draw on real evaluation work to explore these questions practically. The session also refers to Jewlya Lynn's recent presentation on the Thai seafood retrospective, which raised something we've been thinking about a lot: how practitioners assess the robustness of evidence behind each causal connection.
Bring your own experiences, we'd love to hear how others are navigating this!
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Steve Powell
Co-founder and Director
Causal Map
Gabriele Caldas Cabral
Outreach Coordinator
Causal Map
4/14/26 @ 11:00am ET
Tackling Complexity with AI: A 10-Year Causal Mapping Analysis of Systems Change
Materials
What does it take to understand a decade of systemic change across governments, global brands, civil society, philanthropy, and migrant worker leaders? This Coffee Break explores how a ten-year retrospective of forced labor reforms in Thailand’s seafood industry was analyzed using causal mapping and historical analysis to trace not just what changed, but how, why, and under what conditions change accelerated, stalled, or reversed. Drawing heavily from the study’s methods, we’ll unpack how over 150 documents, stakeholder interviews, focus groups with worker leaders, and stakeholder validation sessions were woven into a dynamic causal analysis. We’ll also examine how AI was intentionally used to augment, not replace, human judgment in identifying patterns across time, testing causal pathways, and strengthening analytic rigor. Join us for a behind-the-scenes look at how we make sense of complexity at scale.
Jewlya Lynn
Policy Solve
11/18/25 @ 11:00am ET
Exploring Causality when Measuring Systems Change: Examples from The Freedom Fund
Materials
The coffee break session will be led by Dr. Elizabeth Anderson (Head of Research and Evaluation, The Freedom Fund) and Dr. Helen Shipman (Independent Consultant). The session responds directly to a frequently raised question: How can I bring causal pathways evaluative approaches into complex, messy systemic change work? The Freedom Fund's concrete, actionable ways of evaluating systemic change with a causal lens will be shared and brought to life through two example evaluations that examine how and why change happened as The Freedom Fund and its partners sought to address exploitative child domestic work in Ethiopia.
Elizabeth Anderson
The Freedom Fund
Helen Shipman
Independent Consultant
7/3/25 @ 11:00am ET
Attending to quality and rigour throughout causal pathways evaluation
Materials
Appropriate definitions and processes to support quality and rigour in non-experimental evaluation is a concern that theory based and participatory evaluation communities are actively engaged in. In this webinar we introduced guidance developed by the Causal Pathways initiative aimed at evaluation and learning officers in philanthropic foundations, situating the guidance and practice in broader debates on values-driven and use-oriented evaluation.
Marina Apgar
Institute of Development Studies
Tom Aston
Independent Consultant
Megan Shoji
Mathematica
Slides
4/9/25 @ 11:00am ET
Strengthening Outcome Harvesting Analysis with AI-Assisted Causal Mapping
Materials
Heather Britt
Steve Powell
Gabriele Caldas
Enhance Outcome Harvesting analysis with AI-assisted Causal Mapping. In this coffee break, Heather Britt, Steve Powell and Gabriele Caldas discuss their pilot to enhance analysis of causal relationships in Outcome Harvesting. Their pilot demonstrated that AI-assisted Causal Mapping can reveal interrelationships between outcomes and identify new actors contributing to change. They describe the pilot process, explain how they interpreted the findings, and share five practical tips. A principle-led analysis plan and the right human expertise are key to in guiding the use of AI in analysis.
Causal Map
Causal Map
Independent Consultant
Slides
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