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The top 2% researchers list from Professor John P. A. Ioannidis from Stanford University captures a lot of attention worldwide. Professor Ioannidis introduced a new marker to evaluate a researcher’s contributions named the composite score (C-Score). The C-Score provided an excellent metric to determine where an author stands in comparison to others within the global research community. However, while the C-Score effectively ranks researchers, it is not particularly helpful for new researchers seeking to evaluate potential mentors or guides. Emerging researchers want to know if potential mentors prioritize quantity or quality. They also seek clarity about research output requirements when joining a team.

Objective

We address this gap with The Research Mind framework. It introduces two new metrics: the S-Score (measures research quantity and productivity) and the Q-Score (measures research quality and impact). These metrices help new researchers choose mentors wisely by going beyond traditional ranking systems.

Methods

We developed the S-Score to measure maximum average first-author publications over any three-year period. This provides insights into productivity expectations. We also created the Q-Score to evaluate maximum median citations for first/last author works over three years. This indicates research quality and impact. Additionally, we implemented comprehensive self-citation analysis to assess research integrity. The framework was built using OpenAlex database and includes network analysis capabilities for collaboration pattern visualization.

Results

Our analysis uncovered significant differences between C-Score rankings and a researcher’s suitability for mentorship. We found that some researchers had high C-Scores but also had S-Scores of 10, meaning they published 10 papers per year. This is an unusually high productivity rate that may be unsustainable for most researchers. In contrast, researchers publishing one paper per year had Q-Scores above 50, making them potentially better mentors for quality-focused research. Our self-citation analysis revealed concerning patterns, with high self-citation rates (>20%) indicating potentially problematic research practices.

Conclusion

The Research Mind framework provides essential complementary metrics to Ioannidis’s C-Score system, enabling new researchers to evaluate potential guides/mentors based on productivity expectations (S-Score) and quality focus (Q-Score) rather than solely on composite rankings. This approach will help emerging researchers identify mentors whose research philosophy and output expectations align with their career goals and capabilities. Hence, The Research Mind framework addresses a critical gap in academic mentorship selection.

To facilitate widespread adoption and accessibility, we have developed a comprehensive web application. This app allows researchers to easily search, analyze, and compare these metrics for any author/researcher. The platform is freely available at www.theresearchmind.com/trm-app , providing an intuitive interface for exploring S-Scores, Q-Scores, self-citation patterns, collaboration networks, and overall evaluation metrics to support informed academic decision-making.

PVLDB Reference Format

Sanjay Rathee and Chanchal Chaudhary. The Research Mind: A Multi-Dimensional Framework for Evaluating Research Quality, Productivity, and Integrity by Mitigating citation bias. PVLDB, 14(1): XXX-XXX, 2020. doi:XX.XX/XXX.XX

PVLDB Artifact Availability

The source code, data, and/or other artifacts have been made available at URL_TO_YOUR_ARTIFACTS.