Author position ratio (APR): a simple complementary bibliometric descriptor of authorship patterns

• Introduces the Author Position Ratio (APR), a simple descriptor of authorship patterns based solely on byline position. • Classifies researchers into authorship typologies, providing a qualitative identity rather than a numerical credit weight. • Reveals authorship strategies that remain hidden in traditional citation indices such as the h-index and c-score. • Combining APR with citation metrics enhances the interpretive clarity and transparency of bibliometric evaluation. • Offers a fully operational easy to compute method with no arbitrary assumptions, including graphical representation for immediate visual interpretation. Assessing an individual researcher’s contribution using single-number citation metrics is challenging, especially in the context of increasingly multi-authored publications. Existing indices, whether simple or composite, often overlook authorship patterns and provide limited insight into each author’s actual involvement in research and publication tasks. Attempts to standardize credit allocation, such as the CRediT taxonomy, rely on self-reported information and are prone to subjectivity, while position-weighted citation metrics typically depend on arbitrary assumptions, discipline-specific conventions, or computationally intensive modeling. This paper introduces the author position ratio (APR), a simple, semiquantitative, and field-independent descriptor specifically designed to complement citation-based indicators by capturing career-long authorship patterns. The APR classifies each scholar according to the relative prevalence of single/first, intermediate, and last authorship—corresponding to author, collaborator, and manager strategies—and expresses the dominant pattern through an alphanumeric code and a ternary graphical representation. The method is illustrated through hypothetical examples and applied to real data from the 500 paleontologists included in the 2025 Stanford ranking of highly influential scientists. The results show that APR categories reveal substantial heterogeneity in authorship strategies that remains hidden in traditional bibliometric indicators: researchers with similar h-indices or c-scores may exhibit markedly different authorship profiles. Combining APR descriptors with citation metrics enriches the interpretation of scientific performance by contextualizing impact measures within authorship roles. Because it requires only byline information, avoids arbitrary weighting schemes, and yields intuitive numerical and graphical outputs, the APR offers a transparent and easily applicable complement for evaluation practices and research assessment frameworks.