• Replicate past work. Currently, we do not have enough studies to contribute to a deeply informative meta-analysis. We are attempting to converge studies that use entirely different mediums and appeals, that are implemented over entirely different timeframes, and that measure entirely different outcome variables. This diversity at first appears to be a benefit, allowing us to distill findings across the full spectrum of reduction/elimination interventions — from leaflets to university courses to eco-labels on cafeteria offerings. However, in doing so, we limit our ability to adequately distinguish between interventions. Splitting up the data to only compare like with like does not solve the problem either. For example, if we opted to only look at “health appeal” interventions, we would be left with a mere six interventions to analyze. Or if we wished to investigate interventions whose medium is a university class session, module, or course, we would only have three interventions at our disposal.
  
  For a robust meta-analysis that is able to capture both the forest and the trees, more studies are needed — and not just more studies, but more studies that resemble one another. To assess whether eco-labels on food products trigger an uptick in chicken or fish consumption (i.e., small body replacement), we simply need more eco-label studies. To assess whether health is an effective appeal — which does not backfire by increasing small-bodied animal consumption — we need more studies using a health appeal. So on and so forth. In essence, we need more replication studies, studies at least similar enough in concept and execution that we are comparing Honeycrisp and Golden Delicious rather than apples and oranges. For more on this, please see our Conclusions.
• Make use of this report’s accompanying resources. This recommendation is two-fold. First, we highly encourage researchers to use our open-sourced data to expand investigations into the small body problem. Researchers can download our datasets, include additional studies as they are published, and use our R script to run analyses. As the number of relevant studies grows, robust and nuanced analyses of the small body problem become possible. The investigations within this report are merely the first foray.

We believe our data complements existing meat reduction intervention databases (e.g., these by Rethink Priorities and LIME), as ours specifies granular details per study, including but not limited to the body size/species of the animal products consumed. However, we would like to note that LIME’s features in particular are still expanding. LIME currently allows users to conduct their own meta-analyses directly in the platform, based on various outcome and intervention characteristics that can be toggled on and off. All types of meat are currently aggregated, meaning that, at the time of writing, this tool cannot be used to investigate the small body problem. However, this tool is still in beta, with new features being actively added. We highly encourage researchers to explore the site.

Second, we encourage researchers to use our materials in other contexts, wherever they find relevant. Our datasets offer detailed information across a litany of studies, from quantitative data points (e.g., means and sample sizes) to qualitative characteristics (e.g., each intervention’s medium, timeframe, and appeal). This collated information can be used outside of the small body problem context, and we hope advocates will take full advantage.