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A Quantitative Perspective on Ethics in Large Team Science

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Abstract

The gradual crowding out of singleton and small team science by large team endeavors is challenging key features of research culture. It is therefore important for the future of scientific practice to reflect upon the individual scientist’s ethical responsibilities within teams. To facilitate this reflection we show labor force trends in the US revealing a skewed growth in academic ranks and increased levels of competition for promotion within the system; we analyze teaming trends across disciplines and national borders demonstrating why it is becoming difficult to distribute credit and to avoid conflicts of interest; and we use more than a century of Nobel prize data to show how science is outgrowing its old institutions of singleton awards. Of particular concern within the large team environment is the weakening of the mentor–mentee relation, which undermines the cultivation of virtue ethics across scientific generations. These trends and emerging organizational complexities call for a universal set of behavioral norms that transcend team heterogeneity and hierarchy. To this end, our expository analysis provides a survey of ethical issues in team settings to inform science ethics education and science policy.

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Notes

  1. It is important to note that the intellectual property rights associated with a patent are also shared across all \(a\) coapplicants (coinventors and/or coassignees). Because patenting is based upon proof-of-principle and not necessarily implementation, at the least, the commercial rights only need belong to the person(s) who originated the idea. Furthermore, due to the possibility of direct financial benefits attached to the patent rights, there is a tendency to keep coapplicant lists from reaching extreme sizes. Since only the idea is necessary, and prospects of large financial reward are understood, industries encourage patenting ideas almost as quickly as they are generated. Nevertheless, because most ideas are never implemented, there is little incentive to include people with potential downstream contributions (e.g., those who eventually would implement the idea and/or test it). These reasons account for the significantly smaller team sizes and growth rates in patents with respect to scientific publications. Nevertheless, recent policies in companies and academic and government institutions requiring the pre-assignment of an employee’s future intellectual property to the employer may be responsible for a systematic shift away from single-applicant patents.

  2. Interestingly, the United States is the first country to be eliminated from the giant spanning cluster network for \(g_{c}>1.34\). This feature follows from the fact that the US has long been a collaboration hub, having already a large \(M_{ij}(1995)\) for all the countries shown. Hence, the percent growth of counties within the US portfolio is relatively small due to upper limits in the amount that collaboration can increase. Nevertheless, China, Singapore, Turkey, and Iran show signs of significant integration with US research over the 15 year period.

  3. In the natural sciences, the first and corresponding author(s) are typically distinguished from other coauthors. In economics alphabetical ordering of the coauthor list is often the norm, thus eliminating special credit for the lead author and principal investigator. Furthermore, in economics it is common that graduate student data collectors and data cleaners are not included in the coauthor list and only acknowledged in a footnote.

  4. These numbers reflect the number of funded individuals, and so do not account for the unfunded population, which by inverting the success rates provides a rough estimate that the unfunded population has increased by 22 % over the same period. This scenario is further exacerbated by the fact that a small number of principal investigators (6 % of senior scientists) receive a disproportionate amount of the annual funding (28 %) provided through NIH grants (Couzin-Frankel 2014).

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Acknowledgments

We would like to thank Sarah K. A. Pfatteicher for her helpful feedback, as well as the anonymous referees. AMP acknowledges support from the IMT Lucca Foundation and support from the Italian PNR project “CRISIS Lab”. IP and IS acknowledge support by the National Science Foundation via grant # 1135357, entitled “EESE-Experiencing Ethics”. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.

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  1. Laboratory for the Analysis of Complex Economic Systems, IMT Lucca Institute for Advanced Studies, 55100, Lucca, Italy

    Alexander M. Petersen

  2. Computational Physiology Laboratory, University of Houston, Houston, TX, 77204, USA

    Ioannis Pavlidis

  3. College of Natural Sciences and Mathematics, University of Houston, Houston, TX, 77204, USA

    Ioanna Semendeferi

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  1. Alexander M. Petersen
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Correspondence to Alexander M. Petersen.

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Petersen, A.M., Pavlidis, I. & Semendeferi, I. A Quantitative Perspective on Ethics in Large Team Science. Sci Eng Ethics 20, 923–945 (2014). https://doi.org/10.1007/s11948-014-9562-8

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