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arXiv · 2501.17150

Cultural Differences and Perverse Incentives in Science Create a Bad Mix: Exploring Country-Level Publication Bias in Select ACM Conferences

Abstract

In the era of big science, many national governments are helping to build well-funded teams of scientists to serve nationalistic ambitions, providing financial incentives for certain outcomes for purposes other than advancing science. That in turn can impact the behavior of scientists and create distortions in publication rates, frequency, and publication venues targeted. To that end, we provide evidence that indicates significant inequality using standard Gini Index metrics in the publication rates of individual scientists across various groupings (e.g. country, institution type, ranking-level) based on an intensive analysis of thousands of papers published in several well-known ACM conferences (HRI, IUI, KDD, CHI, SIGGRAPH, UIST, and UBICOMP) over 15 years between 2010 to 2024. Furthermore, scientists who were affiliated with the top-5 countries (in terms of research expenditure) were found to be contributing significantly more to the inequality in publication rates than others, which raises a number of questions for the scientific community. We discuss some of those questions later in the paper. We also detected several examples in the dataset of potential serious ethical problems in publications likely caused by such incentive systems. Finally, a topic modeling analysis revealed that some countries are pursuing a much narrower range of scientific topics relative to others, indicating those incentives may also be limiting genuine scientific curiosity. In summary, our findings raise awareness of systems put in place by certain national governments that may be eroding the pursuit of truth through science and gradually undermining the integrity of the global scientific community.

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BibTeXRIS

Aksheytha Chelikavada, Casey C. Bennett. 2025-03-14. Cultural Differences and Perverse Incentives in Science Create a Bad Mix: Exploring Country-Level Publication Bias in Select ACM Conferences. https://arxiv.org/abs/2501.17150

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