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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| Online Access: | https://arxiv.org/abs/2502.03623 |
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| _version_ | 1866915141326471168 |
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| author | Yang, Lulin Ginther, Donna K. Wu, Lingfei |
| author_facet | Yang, Lulin Ginther, Donna K. Wu, Lingfei |
| contents | In an ideal world, every scientist's contribution would be fully recognized, driving collective scientific progress. In reality, however, only a few scientists are recognized and remembered. Sociologist Robert Merton first described this disparity between contribution and recognition as the Matthew Effect, where citations disproportionately favor established scientists, even when their contributions are no greater than those of junior peers. Merton's work, however, did not account for coauthored papers, where citations acknowledge teams rather than individual authors. How do teams affect reward systems in science? We hypothesize that teams will divide and obscure intellectual credit, making it even harder to recognize individual contributions. To test this, we developed and analyzed the world's first large-scale observational dataset on author contributions, derived from LaTeX source files of 1.6 million papers authored by 2 million scientists. We also quantified individual credits within teams using a validated algorithm and examined their relationship to contributions, accounting for factors such as team size, career stage, and historical time. Our findings confirm that teams amplify the Matthew Effect and overshadow individual contributions. As scientific research shifts from individual efforts to collaborative teamwork, this study highlights the urgent need for effective credit assignment practices in team-based science. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_03623 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Large Teams Overshadow Individual Recognition Yang, Lulin Ginther, Donna K. Wu, Lingfei Social and Information Networks H.2.8; J.4 In an ideal world, every scientist's contribution would be fully recognized, driving collective scientific progress. In reality, however, only a few scientists are recognized and remembered. Sociologist Robert Merton first described this disparity between contribution and recognition as the Matthew Effect, where citations disproportionately favor established scientists, even when their contributions are no greater than those of junior peers. Merton's work, however, did not account for coauthored papers, where citations acknowledge teams rather than individual authors. How do teams affect reward systems in science? We hypothesize that teams will divide and obscure intellectual credit, making it even harder to recognize individual contributions. To test this, we developed and analyzed the world's first large-scale observational dataset on author contributions, derived from LaTeX source files of 1.6 million papers authored by 2 million scientists. We also quantified individual credits within teams using a validated algorithm and examined their relationship to contributions, accounting for factors such as team size, career stage, and historical time. Our findings confirm that teams amplify the Matthew Effect and overshadow individual contributions. As scientific research shifts from individual efforts to collaborative teamwork, this study highlights the urgent need for effective credit assignment practices in team-based science. |
| title | Large Teams Overshadow Individual Recognition |
| topic | Social and Information Networks H.2.8; J.4 |
| url | https://arxiv.org/abs/2502.03623 |