**5. Conclusions**

This paper developed an analytical framework for clarifying the notion of social learning, which reveals its plural forms and teases out its coevolutionary relationship with TD coproduction efforts for sustainability transitions. A social practice perspective illuminates the material and nonmaterial dimensions of this relationship. In decoupling these properties from individual human agency, the SPT perspective affords a means of tracing their emergence in different groups and social contexts, generating a deeper understanding of how social learning arises and effects change.

This conceptualization of social learning was explored in the context of a real-world case—a Toronto-based TD coproduction effort that convened leaders of small-scale interventions working in the region's climate action space as well as key funders of their efforts and researchers. Applying the analytical framework to this process demonstrated that the diverse array of practice elements afforded by the TD coproduction effort helped to both spur and embody social learning while simultaneously being shaped and reconstituted by social learning.

Building on one of the core insights of this analytical framework—the need to operationalize social learning and the potential to do so through a novel evaluation approach—informs a future research agenda investigating how this might best be undertaken in the context of neighbourhood-scale interventions striving to realize bold sustainability aims.

**Author Contributions:** Conceptualization, K.S. and J.R.; data curation, K.S.; formal analysis, K.S. and J.R.; funding acquisition, J.R. and K.S.; investigation, K.S. and J.R.; methodology, J.R. and K.S.; project administration, K.S.; resources, J.R.; software, K.S.; supervision, J.R.; validation, J.R.; visualization, K.S. and J.R.; writing—original draft, K.S.; writing—review and editing, J.R. and K.S. Both authors have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by The Atmospheric Fund (TAF), grant number 506108, and the University of Toronto by way of the corresponding author's PhD funding package.

**Acknowledgments:** The authors wish to gratefully acknowledge funding for this research project from The Atmospheric Fund and the University of Toronto. As a community-engaged research project employing a coproduced evaluation approach, we are grateful to our project partners who generously contributed their time, knowledge and insights to this project. Finally, we wish to thank members of our research group, namely, Grégoire Benzakin and Pani Pajouhesh at the University of Toronto, who were instrumental in developing the framework used in this paper.

**Conflicts of Interest:** In accordance with the principles of coproduction, all evaluation framework users, including the funder, contributed to the design of the study, the creation of the framework and the interpretation of results.
