Scientific Output and Recognition: A Study in the Operation of the Reward System in Science

Cole, Stephen; Cole, Jonathan R.

doi:10.2307/2091085

Cited by 569 publications

(273 citation statements)

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“…This narrative shapes expectations of faculty across career stages, and publication counts have been shown to impact both tenure decisions [2,3], and the ability to secure funding for future research [4]. In this study, we showed that the conventional narrative, while intuitive, and certainly applicable to averages of many professors, is a remarkably inaccurate description of most professors' trajectories.…”

Section: Discussionmentioning

confidence: 83%

The misleading narrative of the canonical faculty productivity trajectory

Way

Morgan

Clauset

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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A scientist may publish tens or hundreds of papers over a career, but these contributions are not evenly spaced in time. Sixty years of studies on career productivity patterns in a variety of fields suggest an intuitive and universal pattern: productivity tends to rise rapidly to an early peak and then gradually declines. Here, we test the universality of this conventional narrative by analyzing the structures of individual faculty productivity time series, constructed from over 200,000 publications and matched with hiring data for 2453 tenure-track faculty in all 205 Ph.D-granting computer science departments in the U.S. and Canada. Unlike prior studies, which considered only some faculty or some institutions, or lacked common career reference points, here we combine a large bibliographic dataset with comprehensive information on career transitions that covers an entire field of study. We show that the conventional narrative confidently describes only one fifth of faculty, regardless of department prestige or researcher gender, and the remaining four fifths of faculty exhibit a rich diversity of productivity patterns. To explain this diversity, we introduce a simple model of productivity trajectories, and explore correlations between its parameters and researcher covariates, showing that departmental prestige predicts overall individual productivity and the timing of the transition from first-to last-author publications. These results demonstrate the unpredictability of productivity over time, and open the door for new efforts to understand how environmental and individual factors shape scientific productivity. INTRODUCTIONScholarly publications serve as the primary mode of communication through which scientific knowledge is developed, discussed, and disseminated. The amount that an individual researcher contributes to this dialoguetheir scholarly productivity-thus serves as an important measure of the rate at which they contribute units of knowledge to the field, and this measure is known to influence the placement of graduates into faculty jobs [1], the likelihood of being granted tenure [2,3], and the ability to secure funding for future research [4].The trajectory of productivity over the course of a researcher's lifetime has been studied for at least 60 years, with the common observation being that a researcher's productivity rises rapidly to a peak and then slowly declines [5][6][7][8][9], which has inspired the construction of mechanistic models with a similar profile [7,[9][10][11][12]. These models have included factors like cognitive decline with age, career age, finite supplies of human capital, knowledge advantages conferred by recent education, as well as skill deficits among the young, among others, and have been supported by the observation that individual productivity curves feature both long-and medium-term fluctuations [12] and are not well described by even fourth-degree polynomial models [9]. Indeed, every study we found to date proposes or confirms a * samuel.way@colorado.edu † allison.morg...

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Section: Discussionmentioning

confidence: 83%

The misleading narrative of the canonical faculty productivity trajectory

Way

Morgan

Clauset

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…At a level of zero citations the margimd value (in 1984 dollars) of a citation to a nonfirst-author article is$314 whife that of a citation to a first-author source is $402. 5 Note, however, that the explanatory power, as measured by the coefficient of determination, is the same for lmth Regression (2) and Regression (3). A tentative inference from this rlnding is that the less-costly-WotXaintirat-author citations may suffice if the objective is mairdyto predict salaries (sa also Roy et al 1983).…”

Section: Totaf Vs First-aaathor-qnfy Citation Countsmentioning

confidence: 83%

Opening access by overcoming Zeno’s paralysis

Harnad¹

2006

Open Access

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“…We next write the discrete-time discrete-space master equation in the continuous-time discrete-space form ∂Pðx þ 1;tÞ ∂t ¼ gðxÞPðx;tÞ − gðx þ 1ÞPðx þ 1;tÞ; [10] where gðxÞ ¼ f ðxÞ∕δt and t ¼ Nδt (for an extensive discussion of master equation formalism, see ref. 48).…”

Section: Appendix: the Spatial Poisson Distributionmentioning

confidence: 99%

Quantitative and empirical demonstration of the Matthew effect in a study of career longevity

Petersen

Jung

Yang

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

229

239

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The Matthew effect refers to the adage written some two-thousand years ago in the Gospel of St. Matthew: "For to all those who have, more will be given." Even two millennia later, this idiom is used by sociologists to qualitatively describe the dynamics of individual progress and the interplay between status and reward. Quantitative studies of professional careers are traditionally limited by the difficulty in measuring progress and the lack of data on individual careers. However, in some professions, there are well-defined metrics that quantify career longevity, success, and prowess, which together contribute to the overall success rating for an individual employee. Here we demonstrate testable evidence of the age-old Matthew "rich get richer" effect, wherein the longevity and past success of an individual lead to a cumulative advantage in further developing his or her career. We develop an exactly solvable stochastic career progress model that quantitatively incorporates the Matthew effect and validate our model predictions for several competitive professions. We test our model on the careers of 400,000 scientists using data from six high-impact journals and further confirm our findings by testing the model on the careers of more than 20,000 athletes in four sports leagues. Our model highlights the importance of early career development, showing that many careers are stunted by the relative disadvantage associated with inexperience. T he rate of individual progress is fundamental to career development and success. In practice, the rate of progress depends on many factors, such as an individual's talent, productivity, reputation, as well as other external random factors. Using a stochastic model, here we find that the relatively small rate of progress at the beginning of the career plays a crucial role in the evolution of the career length. Our quantitative model describes career progression using two fundamental ingredients: (i) random forward progress "up the career ladder" and (ii) random stopping times, terminating a career. This model quantifies the "Matthew effect" by incorporating into ingredient (i) the common cumulative advantage property (1-8) that it is easier to move forward in the career the further along one is in the career. A direct result of the increasing progress rate with career position is the large disparity between the numbers of careers that are successful long tenures and the numbers of careers that are unsuccessful short stints.Surprisingly, despite the large differences in the numbers of long and short careers, we find a scaling law that bridges the gap between the frequent short and the infrequent long careers. We test this model for both scientific and sports careers, two careers where accomplishments are methodically recorded. We analyze publication careers within six high-impact journals: Nature, Science, the Proceedings of the National Academy of Science (PNAS), Physical Review Letters (PRL), New England Journal of Medicine (NEJM), and CELL. We also analyze sports careers within ...

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Scientific Output and Recognition: A Study in the Operation of the Reward System in Science

Cited by 569 publications

References 0 publications

The misleading narrative of the canonical faculty productivity trajectory

The misleading narrative of the canonical faculty productivity trajectory

Opening access by overcoming Zeno’s paralysis

Quantitative and empirical demonstration of the Matthew effect in a study of career longevity

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