Our Website Backgrounds (2).jpg

PRIORITIZING IDEAS

This is one of the documents on Charity Entrepreneurship’s 2019/2020 research process. ​A summary of the full process is here.

Table of contents:

1. Goal

2. Explanation
3. Method

 

1. GOAL


Ordering the top one hundred ideas so that ~20–50 percent of them can be researched in more depth.

2. EXPLANATION

We will order ideas from the most promising to the least promising for a given cause. In this process, no ideas are ruled out completely, but probably only the top third will be researched more deeply this round.

 

3. METHOD

Our cause area order process can warrant more time being put into a large number of ideas. It also has some methodological changes when compared to our idea sort report or our deep dive report. For each idea, we are now able to put two hours into evaluating it (in addition to the four five-minute methodologies that were put into it in the idea sort). For each idea, the full two hours will be put into one methodology, with that methodology differing depending on the cause. This is sacrificing a breadth of approaches for a high level of depth on a single approach. We did this because we did not feel like a thirty-minute version of each of the four methodologies would generate a sufficiently different result from the idea sort methodology. 

A two-hour approach is applied at the level of a specific idea within a given cause instead of for a cause as a whole. Research on a specific idea will be sufficient to build a simple model or estimate: for example, talking to an expert in social and behavioral change radio campaigns instead of talking to an expert focused on family planning as a whole who needs to give input on a large number of ideas.
 

  • Animals – two-hour WFM 

  • Health policy – two-hour IC 

  • Mental health – two-hour CEA 

  • Family planning – two-hour EpV 


Animals and weighted factor model: Because of the limited evidence base, animals are a tricky space to make judgments on without getting multiple sources of information both because the experts are fairly divided and because there are few hard data with which to create a CEA. Additionally, using the same methodology allows a more direct comparison with last year’s recommended animal charities, which were primarily evaluated using a WFM (although the model included factors like cost-effectiveness and EpV). 

Health policy and informed consideration: We believe health policy will be both the most complex and most widely varying issue we will look into. As such, it is less conducive to a more rigid methodology such as weighted factor or CEA. In this area, we also expect to find unusually high expert disagreement, due partly to the complexity of the issue and partly to the emotional salience policies have with many experts. 

Mental health/happiness and cost-effectiveness analysis: We expect mental health/happiness to have very wide ranges of cost effectiveness between different interventions, and there are some cost effectiveness-focused models in the area but, where available, they measure outcomes in Quality-Adjusted Life Years (QALYS) and only examine cost effectiveness in terms of willingness to pay for QALYS rather than with the intention of comparisons. This suggests some large gains from making these models in the second round because this information would be hard to attain from other sources and is not generally considered in the same way by experts.

Family planning and expert views: Here, experts seem to have more cross agreement than in the other areas we considered. This means we can both rely on experts’ judgment and draw conclusions due to their agreement. Additionally, we believe that many interventions have a number of organizations executing them, hence allowing for informed discussions on their logistics.

Publishing plan
We will publish a list of all interventions considered as well as a one-paragraph summary as to why the idea is ranked where it is compared to other ideas. This will be somewhat similar to our previous published paragraphs on ruled-out areas.