The relevance of case studies in climate change research: a review of policy recommendations

Abstract

In the age of big data, case studies build the foundation for the large-scale models that are increasingly being used for decision and policymaking. In this systematic literature review, we investigated the geographic, methodological, and conceptual characteristics of case studies in climate change science to evaluate the extent they provide policy recommendations to answer the questions: how can researchers best gather and report policy-relevant information for climate change adaptation, resilience, and/or recovery? What are the current themes within the literature, and how can these areas best advance as policy-relevant fields within climate change science? Findings highlight that policy recommendations were more robust, and significantly more likely, in case studies that employ participatory research methods; and geographic characteristics and use of theoretical frameworks are associated with providing policy recommendations. On the other hand, studies that focus on biophysical parameters of climate change offered weak or no policy recommendations. Thus, we conclude that local-level case study research can serve as validation and calibration data for large-scale models as long as they accurately represent the local values and perceptions of the people in the study area. We elaborate on the opportunities that exist in non-human, biophysical, research for communicating findings to policy-friendly audiences.

Recommending Reform: A Critical Race and Critical Policy Analysis of Research Recommendations About School Resource Officers

“…Schwab found that although recommendations for improving Indigenous Edu-cation have become sharper over time, the recommendations themselves were remarkably consistent, suggesting that many of the underlying issues of equity, access, and participation, had continued unresolved over the 20-year period. In climate science, Teodoro et al (2019) studied the methodological decisions that generated robust reco-mmendations and found that the robustness was connected to methodologies that considered context. Outside of these examples, we could identify no others that directly analyzed research recommendations.…”