Call for Projects – Soft Launch
There is a tension between collecting predictions for more studies and risking survey fatigue on the part of expert forecasters. One of the biggest challenges in building a predictions platform for social science research is that it might impose a large burden on forecasters, similar to providing the public good of referee reports. An advantage of a centralized predictions platform is that we can ensure no individual receives an abundance of requests for predictions. To further mitigate risk, our “soft launch” of this platform will focus on gathering predictions for a few key initial studies. This will enable us to tweak parameters like the incentives offered and the frequency of prediction requests and adapt going forward.
To reduce the risk of forecasts being biased by study results, it is best if data has yet to be collected or if results are not yet available or accessible. For example, projects that have been offered “in-principle acceptance” as part of a Registered Reports track but have not yet collected data might be particularly suitable. Forecasts may also be particularly useful for large, flagship projects that are unlikely to be replicated.
Initially, we will focus mainly on economics topics with the eventual goal of opening the platform to other social sciences.
The benefits to researchers of collecting forecasts include:
- Freedom to describe their project and determine what questions are asked of forecasters.
- Forecasts elicited from a sample of experts, including (i) disciplinary experts (e.g., pre-screened PhD students), (ii) selected experts curated for particular topics or methods (e.g., senior academics and professionals), and (iii) members of the general public who sign up on the platform.
- Funding for forecasting incentives and research assistance.
- Assistance with designing your elicitation surveys.
- Early feedback to help determine which treatments or outcomes to prioritize.
- Increased visibility of the research project.
We are currently openly soliciting studies to forecast! Please get in touch at email@example.com with a short description of your study and your timeline if you are interested in being featured on the platform. We plan to slowly increase accepted submissions over time as the pool of forecasters grows.