IEF: Anonymous Peer Public Good Impact Measurement

IEF: Anonymous Peer Public Good Impact Measurement

IEF: Empowering Ethereum public good projects through insightful impact evaluation & anonymous peer review. Impact measured, merit rewarded, ecosystem advanced.

The problem IEF: Anonymous Peer Public Good Impact Measurement solves

IEF is a platform designed to enable RetroPGF Round 3 nominees to evaluate a random set of peer nominees projects impact anonymously. Through this evaluation, they can attest to the correct self-evaluation of others and help improve the current information gap badgeholders that are not familiar with a specific category might have.

IEF proposes a 3-step process to address the challenge in measuring the impact of public goods projects applying for RetroPGF. This process is only possible with the creation, and upkeep of an Impact Evaluation Framework that provides opt-in guidelines on a) how KPI's to measure impact are created and measured (at a technical level), b) offers a non-exhaustive set of KPI's that are commonly used by projects to evaluate their impact, and the logic behind those KPI's (these can be used as inspiration on how to create new KPI's), c) the importance of empowering operators to self-assess, d) guidelines to generate both quantitative and qualitative evaluations, e) the dangers of over-meassuring.

This framework will reduce the coordination challenges currently faced by Optimisms Badgeholders, specifically in areas in which they are not experts, but still need to make a funding allocation decision


  1. Submission of a self-reported impact evaluation
  2. Random, anonymous, peer-evaluation
  3. Distribution of a random set of projects for evaluation to badgeholders: the information they will receive is a) self-reported impact + b) Attestation of the peer evaluation.

Leveraging UniRep, IEF ensures that only projects who have submitted a self-reported impact evaluation, and are therefore familiar with the Impact Evaluation Framework, can evaluate peers in an anonymous manner using zero knowledge. It also enables the creation of a carry-on reputation from one evaluation round to the next, per category, without the need for a member to forfeit their anonymity. A random, anonymous evaluation serves to prevent collusion and retaliation of any part.

Challenges I ran into

I'm not a dev :D so forking the UniRep boiler plate was a challenge.

  1. Boilerplate did not support Windows: I have a Windows computer which is not supported by the npx create unirep-app which made it imposible to duplicate the original repo easily.
    Solution: A friend with a Mac helped me review the different files in the folder to check which were missing from the copy made to my Windows folder and I added them manually based on the code in the Mac copy. This debugging took about 5 hours.
  2. Missing dependencies: There were several dependencies that were not listed on UniReps READ ME that for someone who is new to coding, like myself, were fundamental. I noticed other hackers had them pre-installed from previous projects, but since this was my first time using these programs in my computer, I didn't have them and they caused a lot of errors in the process.
  3. No additional functioning examples of UniRep: Canon Party is an implementation of UniRep that would have been incredibly useful for this project, however, the code did not work even when I forked it, and tried to run it locally.

Technologies used