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Scientific authorship has been increasingly complemented with contributorship statements. While such statements are said to ensure more equitable credit and responsibility attribution, they also provide an opportunity to examine the roles and functions that authors play in the construction of knowledge and the relationship between these roles and authorship order. Drawing on a comprehensive and multidisciplinary dataset of 87,002 documents in which contributorship statements are found, this article examines the forms that division of labor takes across disciplines, the relationships between various types of contributions, as well as the relationships between the contribution types and various indicators of authors' seniority. It shows that scientific work is more highly divided in medical disciplines than in mathematics, physics, and disciplines of the social sciences, and that, with the exception of medicine, the writing of the paper is the task most often associated with authorship. The results suggest a clear distinction between contributions that could be labeled as 'technical' and those that could be considered 'conceptual': While conceptual tasks are typically associated with authors with higher seniority, technical tasks are more often performed by younger scholars. Finally, results provide evidence of a U-shaped relationship between extent of contribution and author order: In all disciplines, first and last authors typically contribute to more tasks than middle authors. The paper concludes with a discussion of the implications of the results for the reward system of science.

Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.

Presenting data on all full-length articles in the three top general economics journals for one year in each decade 1960s—2010s, I analyze changes in patterns of coauthorship, age structure and methodology, and their possible causes. The distribution of number of authors has shifted steadily rightward. In the last two decades, the fraction of older authors has almost quadrupled. Top journals are publishing many fewer papers that represent pure theory, regardless of subfield, somewhat less empirical work based on publicly available data sets, and many more empirical studies based on data collected by the author(s) or on laboratory or field experiments.

Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, because the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors’ contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions.

Recent controversies in psychology have spurred conversations about the nature and quality of psychological research. One topic receiving substantial attention is the role of replication in psychological science. Using the complete publication history of the 100 psychology journals with the highest 5-year impact factors, the current article provides an overview of replications in psychological research since 1900. This investigation revealed that roughly 1.6% of all psychology publications used the term replication in text. A more thorough analysis of 500 randomly selected articles revealed that only 68% of articles using the term replication were actual replications, resulting in an overall replication rate of 1.07%. Contrary to previous findings in other fields, this study found that the majority of replications in psychology journals reported similar findings to their original studies (i.e., they were successful replications). However, replications were significantly less likely to be successful when there was no overlap in authorship between the original and replicating articles. Moreover, despite numerous systemic biases, the rate at which replications are being published has increased in recent decades.

This article reports a stylometric study of contemporary French prose from the second half of the 20th century by authors from Europe and Francophone Africa. We test whether classical stylometry, long effective in authorship attribution, can also capture collective properties of large corpora – specifically author gender and cultural origin. Results show that, in fiction, gender detection is highly unreliable: skilled writers can convincingly adopt diverse voices regardless of sociological profile, whereas the same methods often succeed on non-fiction by users (blogs, emails, social media). Likewise, in French prose, analyses based on short lists of neutral function words fail to discriminate European from African authors. Clear separation appears only when long n-gram features are used, which encode culturally inflected vocabulary and contexts. We discuss methodological implications for stylometry beyond attribution.

Research teams are the fundamental social unit of science, and yet there is currently no model that describes their basic property: size. In most fields, teams have grown significantly in recent decades. We show that this is partly due to the change in the character of team size distribution. We explain these changes with a comprehensive yet straightforward model of how teams of different sizes emerge and grow. This model accurately reproduces the evolution of empirical team size distribution over the period of 50 y. The modeling reveals that there are two modes of knowledge production. The first and more fundamental mode employs relatively small, \"core\" teams. Core teams form by a Poisson process and produce a Poisson distribution of team sizes in which larger teams are exceedingly rare. The second mode employs \"extended\" teams, which started as core teams, but subsequently accumulated new members proportional to the past productivity of their members. Given time, this mode gives rise to a power-law tail of large teams (10—1,000 members), which features in many fields today. Based on this model, we construct an analytical functional form that allows the contribution of different modes of authorship to be determined directly from the data and is applicable to any field. The model also offers a solid foundation for studying other social aspects of science, such as productivity and collaboration.

Objectives To assess the prevalence of honorary and ghost authors in six leading general medical journals in 2008 and compare this with the prevalence reported by authors of articles published in 1996.Design Cross sectional survey using a web based questionnaire.Setting International survey of journal authors.Participants Sample of corresponding authors of 896 research articles, review articles, and editorial/opinion articles published in six general medical journals with high impact factors in 2008: Annals of Internal Medicine, JAMA, Lancet, Nature Medicine, New England Journal of Medicine, and PLoS Medicine.Main outcome measures Self reported compliance with International Committee of Medical Journal Editors (ICMJE) criteria for authorship for all authors on the selected articles.Results A total of 630/896 (70.3%) corresponding authors responded to the survey. The prevalence of articles with honorary authorship or ghost authorship, or both, was 21.0% (95% CI 18.0% to 24.3%), a decrease from 29.2% reported in 1996 (P=0.004). Based on 545 responses on honorary authorship, 96 articles (17.6% (95% CI 14.6% to 21.0%)) had honorary authors (range by journal 12.2% to 29.3%), a non-significant change from 1996 (19.3%; P=0.439). Based on 622 responses on ghost authorship, 49 articles (7.9% (6.0% to 10.3%)) had ghost authors (range by journal 2.1% to 11.0%), a significant decline from 1996 (11.5%; P=0.023). The prevalence of honorary authorship was 25.0% in original research reports, 15.0% in reviews, and 11.2% in editorials, whereas the prevalence of ghost authorship was 11.9% in research articles, 6.0% in reviews, and 5.3% in editorials.Conclusions Evidence of honorary and ghost authorship in 21% of articles published in major medical journals in 2008 suggests that increased efforts by scientific journals, individual authors, and academic institutions are essential to promote responsibility, accountability, and transparency in authorship, and to maintain integrity in scientific publication.

A Science investigation has uncovered a smorgasbord of questionable practices including paying for author's slots on papers written by other scientists and buying papers from online brokers. Science has exposed a thriving academic black market in China involving shady agencies, corrupt scientists, and compromised editors—many of them operating in plain view. The commodity: papers in journals indexed by Thomson Reuters' Science Citation Index, Thomson Reuters' Social Sciences Citation Index, and Elsevier's Engineering Index.