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Retraction: The “Other Face” of Research Collaboration?

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Abstract

The last two decades have witnessed the rising prevalence of both co-publishing and retraction. Focusing on research collaboration, this paper utilizes a unique dataset to investigate factors contributing to retraction probability and elapsed time between publication and retraction. Data analysis reveals that the majority of retracted papers are multi-authored and that repeat offenders are collaboration prone. Yet, all things being equal, collaboration, in and of itself, does not increase the likelihood of producing flawed or fraudulent research, at least in the form of retraction. That holds for all retractions and also retractions due to falsification, fabrication, and plagiarism (FFP). The research also finds that publications with authors from elite universities are less likely to be retracted, which is particularly true for retractions due to FFP. China stands out with the fastest retracting speed compared to other countries. Possible explanations, limitations, and policy implications are also discussed.

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Fig. 1

Source: Authors’ data collection from WoS

Fig. 2

Source: Authors’ data collection from WoS

Fig. 3
Fig. 4

Source: Authors’ data collection from WoS

Fig. 5

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Notes

  1. For example, Stern et al. (2014) noted that on average, each retracted article funded by the U.S. National Institutes of Health between 1992 and 2012 incurred an average direct cost of about 392 thousand US dollars.

  2. The ranking order of these countries changes a bit due to different coverage of retraction articles.

  3. Different samples and coding schemes are the two main reasons accounting for the different results between Steen (2011b) and Fang et al. (2012). First, while both used PubMed as the data source, Steen (2011b) covered about 800 retracted articles between 2000 and 2010, while Fang et al. (2012) looked at some 2,000 retracted articles between 1973 and May 2012. Second, Steen (2011b) collapsed “undisclosed reasons” for retraction under the category of errors based on retraction notices, while Fang et al. (2012) improved the research by incorporating information from ORI. It is interesting to note that Steen also is a coauthor of the Fang et al. (2012) paper.

  4. According to Robert Merton (1968), the Matthew Effect refers to the cumulative advantages of renowned scientists who tend to garner more credit than those unknown with equal contributions. In the research of Jin et al. (2013), the term “reverse Matthew Effect” means eminent scholars still win with less credits taken away compared to the less eminent ones who were also punished for retracted articles.

  5. It needs to point out that there is no agreed upon definition on elite scholars, star scientists, senior scholars, or established researchers in extant literature. These terms are often used interchangeably. According to Trikalinos et al (2008) senior scholars refer to professors, lab directors, experienced investigators or researchers who had more than five- year record of publishing original articles. In this research, a dummy variable of Top 100 universities is used as a proxy indicator of an institution’s research status (also see Walsh et al. 2019). For more details please refer to the section of variables.. .

  6. The three major journal indexes of WoS consist of Science Citation Index Expanded, Social Science Citation Index, and Arts & Humanities Citation Index. The data were accessed and downloaded from the libraries at Fudan University and the Shanghai University of Finance and Economics. Taking the difference of research systems into consideration, retractions from Taiwan is not allocated to China in this paper.

  7. This figure is consistent with Fanelli’s (2013) 2294 retractions published from 1901 to 2012. Only retracted original research articles were included for further analysis.

  8. For robustness check, each record was also matched with the journal impact factor (hereinafter JIF) of its publishing year or the nearest available year. For example, for a retracted paper published in 1980, we matched it with 1997s journal impact factor when the earliest JCR report was released. The correlation between these two columns of journal impact factors are as high as 0.99. So the 2012 journal impact factor was chosen for the rest of the analyses. Within the authors’ best knowledge, all previous studies on retractions and journal impact factors used the last available journal impact factor without examining the possible fluctuations of journal impact factor over a long period, or at least this issue was not mentioned in the extant studies [e.g., Steen (2011a) and Furman et al. (2012)]. We would like to thank an anonymous reviewer for his or her insight to direct us toward this examination.

  9. For consistency, non-university institutions such as the Chinese Academy of Sciences and U.S. national laboratories were treated as non-elite.

  10. One retraction notice involving Schön, Kloc, and Batlogg explicitly stated “The committee found one researcher had committed scientific misconduct and cleared the other authors investigated.” The same committee stated in the investigation report on another retracted paper that “based on the preponderance of the evidence, Hendrik Schön committed scientific misconduct as defined by the falsification or fabrication of data, such that the research is not accurately represented in the research record.”.

  11. When only primary authors (i.e., first authors and corresponding authors) are considered, the top five countries with the largest numbers of retracted papers are USA (528), China (310), Japan (243), Germany (145), and India (139). Removing repeat offenders from the sample, the top five countries remain the same, but now Japan and Germany rank after India: i.e., USA (494), China (310), India (139), Japan (127), and Germany (106).

  12. For example, Acta Neurochirurgica (ISSN: 0001-6268) had an impact factor of 1.546 in 2012, which ranked the 126th among 193 journals in the field of clinical neurology, i.e., the third quartile, and 85th of 199 in surgery, i.e., the second quartile.

  13. Only four document types—article, review, note, and letter—are retrieved and used in our investigations.

  14. There are 108 retracted articles with missing values of the publication month for either the retracted article or the retracted notice. Their elapsed months were estimated by assuming the same month of publication and retraction.

  15. Considering the possible stability of ARWU ranking, the rankings of 2014s Top 100 universities in the year of 2003, the earliest year of ARWU rankings, were also downloaded. The comparison reveals that eighty-two of the Top 100 universities listed in 2014 were also in the Top 100 ranking of the year of 2003.

  16. Taking the possible nonlinear effect of collaboration into consideration, we also added squared terms of all three indicators in the regressions. Other robustness tests we conducted include changing any author affiliated with a Top-100 university to a primary author (i.e., first author and reprint author), changing the numerical measurement of collaboration to a set of three dummy variables, excluding retractions due to publisher errors and unknown reasons and their matched records in the regression, and excluding articles coauthored by repeat offenders. Overall, the results remain robust and support the main finding.

  17. This finding is different from that of Furman et al. (2012) in that retraction is uncorrelated with article, author, or institution characteristics. Different data coverage and elite university measurement could lead to this discrepancy. While Furman et al. (2012) focused on medical sciences using data from PubMed between 1977 and 2006, our analysis covered broader fields with data retrieved from WoS for a longer period of time, between 1978 and 2013, thus extending the study of the retraction phenomenon to a much larger retracted group (2087 vs. 677). Furman et al. (2012) controlled for the Top 25 U.S. universities, while we examined the global retraction phenomenon by controlling for the involvement of authors from global Top-100 universities and explicitly measured collaboration through three indicators: number of authors, number of affiliations, and number of countries.

  18. Considering retractions due to FFP, articles with primary authors from Japan also have a larger likelihood of being retracted, as indicated in Panel 2. This may be due to the influence of Japanese repeat offenders as demonstrated in Table 1.

  19. The concern is comparatively less considering international collaboration, as Chinese researchers do not compete against international partners for promotion and research funding. Nonetheless, secondary authorship is highly undervalued for Chinese researchers in the situation of international collaboration.

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Acknowledgements

We would like to thank anonymous reviewers for their comments. We particularly thank Dr. Stephanie J. Bird and Dr. Yvette Pearson for their insightful inputs and careful editing. This research draws on support from the National Natural Science Foundation of China (#71843009; #71774091; #71303147) and the Ministry of Education of China (#20172452). The conclusions contained herein are those of the authors and do not reflect the views of funders.

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Authors and Affiliations

  1. School of International Relations and Public Affairs, Fudan University, Shanghai, 200433, China

    Li Tang

  2. Shanghai University of Finance Economics, Shanghai, 200433, China

    Guangyuan Hu & Yuhan Yang

  3. Kearney A.T, Shanghai, 200433, China

    Yang Sui

  4. College of Finance, Chongqing Technology and Business University, Chongqing, 400067, China

    Yuhan Yang

  5. Faculty of Business, University of Nottingham Ningbo China, Ningbo, 315100, China

    Cong Cao

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  1. Li Tang
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Contributions

Research was designed by LT and GH. Original data downloading, coding and verification were executed by YS, YY, and LT. Analyses were conducted by GH, LT, and CC. Writing was completed by LT, GH and CC.

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Correspondence to Li Tang or Cong Cao.

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Appendices

Appendix 1

See Table 5.

Table 5 Detailed reasons of retraction and illustrative examples.
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Appendix 2

See Table 6.

Table 6 Numbers and shares of retractions by selected countries/regions.
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Tang, L., Hu, G., Sui, Y. et al. Retraction: The “Other Face” of Research Collaboration?. Sci Eng Ethics 26, 1681–1708 (2020). https://doi.org/10.1007/s11948-020-00209-1

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