Decentralized Peer Review in Open Science: A Mechanism Proposal

TL;DR

This paper tackles incentive and transparency gaps in traditional peer review. It proposes a decentralized, community-governed system built on blockchain smart contracts to remunerate reviewers, publish anonymized reports, track reputation, and issue digital certificates. It introduces an information-theoretic paper quality score $Q = $V $\sum_i w_i L_i$ with per-item learning $L_i$ derived from KL-divergence $L_H = D[ P(O|X,A) \;||\; P(O|X) ]$ and a hypothesis/measurement framework. Through tokenomics, governance, and NFT-based provenance, the approach aims to increase review quality and speed while reducing misconduct.

Abstract

Peer review is a laborious, yet essential, part of academic publishing with crucial impact on the scientific endeavor. The current lack of incentives and transparency harms the credibility of this process. Researchers are neither rewarded for superior nor penalized for bad reviews. Additionally, confidential reports cause a loss of insights and make the review process vulnerable to scientific misconduct. We propose a community-owned and -governed system that 1) remunerates reviewers for their efforts, 2) publishes the (anonymized) reports for scrutiny by the community, 3) tracks reputation of reviewers and 4) provides digital certificates. Automated by transparent smart-contract blockchain technology, the system aims to increase quality and speed of peer review while lowering the chance and impact of erroneous judgements.

Figures (1)

• Figure 1: Reputation decay according to \ref{['eq:reputation-decay']} for two scientists, one senior at the end of their career with high initial equilibrium reputation $r=100$ but with decreasing activity $f(t)$ (blue) either to half of the initial $f(0)=20$ over 5 years (solid), or to zero over 10 years (dashed), and one, junior, starting at zero reputation and increasing their activity to the same level $f=20$ level as the senior had initially over a period of 5 years. Here, $k=1/5y$. Thanks to reputation decay it only takes a few years after their contribution rate crosses for reputation to reflect this instead of a full career.