When Excellence Stops Producing Knowledge: A Practitioner's Observation on Research Funding

2026-02-03

AI Summary

This study addresses the growing distortion of “excellence” in research funding systems, where evaluative criteria have become increasingly detached from genuine knowledge production and reduced to performative metrics. Drawing on four decades of peer review experience, the author employs an insider perspective integrating qualitative observation and institutional analysis to demonstrate how the interplay of professionalized grant writing, AI-assisted proposal generation, and a shortage of qualified reviewers exacerbates assessment bias. Invoking Goodhart’s Law, the work elucidates the structural roots of the “excellence paradox,” revealing how the very mechanisms intended to identify merit undermine scientific integrity and systemic efficiency. Moving beyond external critiques, this research systematically unpacks the internal contradictions of contemporary funding regimes, offering policymakers and the academic community a theoretical foundation and actionable pathways for reimagining evaluation frameworks.

Technology Category

• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Search and Optimization: Evaluation and Analysis

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

After almost four decades of participating in competitive research funding -- as applicant, coordinator, evaluator, and panel member -- I have come to see a structural paradox: many participants recognize that the current system is approaching its functional limits, yet most reform measures intensify rather than alleviate the underlying dynamics. This paper documents how excellence has become decoupled from knowledge production through an increasing coupling to representability under evaluation. The discussion focuses on two domains in which this is particularly visible: competitive basic research funding and large EU consortium projects. Three accelerating trends are examined: the professionalization of proposal writing through specialized consultants, the rise of AI-assisted applications, and an evaluator shortage that forces panels to rely on reviewers increasingly distant from the actual research domains. These observations are offered not as external critique but as an insider account, in the hope that naming a widely experienced but rarely articulated pattern may enable more constructive orientation. Keywords: Research funding, Excellence, Evaluation, Goodhart's Law, Professionalization, AI-assisted proposals, Peer review crisis

Problem

• Research funding
• Excellence
• Evaluation
• Goodhart's Law
• Peer review crisis

Innovation

• Excellence
• Evaluation
• Goodhart's Law
• AI-assisted proposals
• Peer review crisis