Blended PC Peer Review Model: Process and Reflection

2025-04-27

AI Summary

Peer review faces three interrelated challenges: reviewer shortages, uneven workload distribution, and decision delays. This paper proposes and empirically validates a hybrid Program Committee (PC) review model in which each submission is assigned to a core triad comprising one junior PC member and two senior PC members, featuring a novel “embedded” collaboration mechanism—junior members engage deeply across the entire review process, not merely as supplementary reviewers. This design simultaneously ensures review quality, fosters early-career researcher development, and enhances community inclusivity. Drawing on empirical process data, post-review author surveys, and comparative reflective analysis—building upon prior Shadow/Junior PC initiatives—the study demonstrates that the Junior PC model significantly alleviates reviewer workload pressure while maintaining high author-rated quality and practical utility of reviews. The work contributes a structured, scalable, and reproducible framework for sustainable peer review governance in academic publishing.

Technology Category

• Natural Language Processing: Interpretability, Analysis, and Evaluation of NLP Models
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Planning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Web Mining and Content Analysis: Models for Web evolution
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

The academic peer review system is under increasing pressure due to a growing volume of submissions and a limited pool of available reviewers, resulting in delayed decisions and an uneven distribution of reviewing responsibilities. To address this challenge, the International Conference on Mining Software Repositories (MSR) 2025 introduced a Blended Program Committee (PC) peer review model for its Technical Track. Building upon the community's earlier experience with the Shadow PC (2021 and 2022) and Junior PC (2023 and 2024), the new model pairs up one Junior PC member with two regular PC members as part of the core review team of a given paper, instead of adding them as an extra reviewer. This paper presents the rationale, implementation, and reflections on the model, including insights from a post-review author survey evaluating the quality and usefulness of reviews. Our findings highlight the potential of Junior PCs to alleviate reviewer shortages, foster inclusivity, and sustain a high-quality peer review process. We offer lessons learned and recommendations to guide future adoption and refinement of the model.

Problem

• Addressing peer review delays due to high submission volumes
• Reducing uneven distribution of reviewing responsibilities
• Alleviating reviewer shortages while maintaining review quality

Innovation

• Blended PC model pairs Junior with regular reviewers
• Junior PC members reduce reviewer shortages effectively
• Model enhances inclusivity and review quality sustainably