Publication Productivity among Scientists: A Critical Review

Fox, Mary Frank

doi:10.1177/030631283013002005

Cited by 388 publications

(279 citation statements)

References 0 publications

Supporting

Mentioning

243

Contrasting

Unclassified

Order By: Relevance

“…Professors settle into their research environments, begin training graduate students, and build their cases for promotion and tenure. Similarly, many reasons have been suggested for why productivity might decrease after promotion, including increased service and non-research commitments, declining cognitive abilities, and increased levels of distraction from outside work due to health issues and childcare obligations [35]. Although an average over faculty appears to confirm the stereotyped trajectory of rapid growth, peak, and slow decline, it does not reveal whether this average is representative of the many individual trajectories it averages over, nor does it show how much diversity there might be around the average, and whether that diversity correlates with other factors of interest.…”

Section: Individual Productivity Trajectoriesmentioning

confidence: 99%

The misleading narrative of the canonical faculty productivity trajectory

Way

Morgan

Clauset

et al. 2017

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

View full text Add to dashboard Cite

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...

show abstract

Section: Individual Productivity Trajectoriesmentioning

confidence: 99%

The misleading narrative of the canonical faculty productivity trajectory

Way

Morgan

Clauset

et al. 2017

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

View full text Add to dashboard Cite

show abstract

“…Much previous research (Fox, 1983;Long, 1978;Hilmer and Hillmer, 2007;Park, 2007;Cho, 2007;Kim, 2008;Kim and Bak, 2011) shows a positive correlation with the graduate students' research productivity. Thus, this study applied the 2013 QS World University Ranking to the indices for the reputation of graduate schools, and made the following hypothesis.…”

Section: Explanatory Variablesmentioning

confidence: 90%

“…The halo effects mean the effects from the reputation of institutions or from supervisors (Crane, 1965). Graduate students are affected by the reputation of their institutions (Fox, 1983;Long, 1978;Hilmer and Hillmer, 2007;Park, 2007;Cho, 2007;Kim, 2008;Kim and Park, 2011), and that of their supervisors (Crane, 1965;Reskin, 1979;Long and Mcginness, 1985;Williamson, 2003;Pagils, Green and Bauer, 2006;Hilmer and Hillmer, 2007;Cho, 2007;Kim, 2008;Kim andBak, 2011, Jang, 2013).…”

Section: Graduate Studentsmentioning

confidence: 99%

“…Many studies (Fox, 1983;Jang et al, 2012;Kim, 2008;Crane, 1965;Reskin, 1979;Cardoso et al, 2008;Lariviere, 2013) use the number of publications as the indices for research productivity of scientists and that of graduate students as well. This study also defines articles published in the SCI journals as research productivity.…”

Section: Variable Of Research Productivitymentioning

confidence: 99%

See 1 more Smart Citation

Research Productivity of Graduate Students in GPF program of Korea

Kim¹

2014

KTIS

View full text Add to dashboard Cite

This study analyzed the factors that influence the research productivity of 236 graduate students who are funded by the Global Ph.D. Fellowship Program of the National Research Foundation of Korea. Research productivity was measured by the number of SCI publications, and the explanatory factors are the demographic factor, the financial factor, the reputation of institutions and the supervisor factor. This study included 2 indices such as the reputation of institutions and the research productivity of supervisors to check the halo effect unlike other studies. Results are as follows: 1) no gender difference, 2) better performance by younger age group, 3) no difference even if the students are additionally funded by other research support programs, 4) no halo effect by the reputation of institution but rather better performance from low ranked universities, 5) and a positive halo effect by supervisors.

show abstract

“…To measure stability, test-retest method was used. To this end, the researcher completed the tool with a two-week interval (Fox, 1983), and compared scores of these two stages using Intra-class Correlation Coefficient (ICC). For homogeneity of the tool, its options were split to two halves and using Spearman-Brown method, correlation between the two halves was examined.…”

Section: Reliability Of the Toolmentioning

confidence: 99%

Psychometric Properties of the Persian Version of the Self-Assessed Support Needs Questionnaire for Breast Cancer Cases

Ghaffari

Shali²,

Shoghi³

et al. 2014

Asian Pacific Journal of Cancer Prevention

View full text Add to dashboard Cite

Background: It has been found that support given to women with breast cancer has a positive effect upon their reactions to the illness and may even prolong their survival. Perceived support needs assessment in breast cancer women could be considered as a necessary part of nursing function. Aim: The purpose of this study was to translate and culturally adapt the self-assessed support needs (SASN) questionnaire into Persian language and to investigate its psychometric properties. Materials and Methods: After forward-backward translation of the questionnaire and making appropriate changes, we selected 160 women with breast cancer as our study sample. The psychometric properties of the SASN, including its internal consistency, test retest reliability, and construct validity were evaluated through the known-groups technique. Results: The calculated Kaiser Meyer Olkin was 0.756, indicating that the sample was sufficiently large to perform a satisfactory factor analysis. The six factors all together explained 50.7% of the variance; the first factor (diagnosing) explaining the biggest part of variance (10.9). Internal consistency reliability was 0.83 for the whole scale and the stability of test was 0.78. For the first factor, Cronbach's alpha was 0.90 and factor loadings of scale's items were found to deal with diagnosis subscale. The domains described patients' diagnosis, treatment, support, femininity and body image, family and friends and information. Conclusions: The reliability and validity of the adapted version of the SASN was shown to be satisfactory. Thus, it can be used to investigate self-assessed support needs of Iranian women suffering from breast cancer since the SASN is a multi-domain scale.

show abstract

Publication Productivity among Scientists: A Critical Review

Cited by 388 publications

References 0 publications

The misleading narrative of the canonical faculty productivity trajectory

The misleading narrative of the canonical faculty productivity trajectory

Research Productivity of Graduate Students in GPF program of Korea

Psychometric Properties of the Persian Version of the Self-Assessed Support Needs Questionnaire for Breast Cancer Cases

Contact Info

Product

Resources

About