Background and Aim. Favoritism in scientific publishing can manifest in various forms of bias toward individual authors, posing a threat to academic fairness and the reputation of scholarly journals. Despite the availability of different expert evaluation methods, the quantitative identification of structural indicators related to uneven publication activity remains an area of practical interest. The aim of the present study is to identify extreme author-level publication concentration patterns within specialized journals on inclusive physical culture using journal-specific normalized indicators. Materials and Methods. The study was based on bibliometric data from journals publishing research related to inclusive physical culture and indexed in the Web of Science Core Collection. Authors’ publication activity was analyzed at the level of individual journals using quantitative indicators reflecting deviations from within-journal publication norms. Journal-specific Z-scores were calculated for each author, and a journal-level rank-based approach combined with the elbow method was applied to identify authors with the most pronounced deviations in publication activity. All data processing and statistical calculations were performed using Python. Results. The analysis revealed substantial variability in author publication activity across journals. Based on journal-specific Z-score distributions, a limited subset of authors exhibited markedly elevated deviations relative to typical within-journal patterns. Application of the elbow method to the ranked Z-scores identified nine authors whose publication activity exceeded the upper inflection threshold (Z-score ≈ 14). These cases were concentrated within a limited number of journals, whereas the majority of journals demonstrated more balanced authorship structures. Conclusions. The proposed approach enables a quantitative assessment of uneven publication activity patterns in scientific journals. The results indicate that the use of normalized publication indicators and data-driven thresholds allows the identification of atypical authorship patterns that may warrant further editorial attention. This framework should be regarded as a preliminary analytical tool and requires complementary validation through contextual and expert-based evaluation.
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Сергій Єрмаков (2026) studied this question.
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