Gender, web presence and scientific productivity in nanoscience and nanotechnology

Sotudeh, Hajar; Khoshian, Nahid

doi:10.1007/s11192-014-1234-6

Cited by 5 publications

(2 citation statements)

References 61 publications

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“…To illustrate this approach, the methodology will be applied to three representative CVs. Note that I will disregard individual characteristics that change over time, such as the researcher's age or position (Cainelli et al, 2012(Cainelli et al, , 2015Morichika & Shibayama, 2015), and individual characteristics that are fixed in time, such as gender or race (Abatemarco & Dell'Anno, 2013;Hopkins et al, 2013;Sotudeh & Khoshian, 2014). In this paper, my interest is in indices for, rather than determinants of, scientific activity (Penner et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

Zagonari

2017

SSRN Journal

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In this study, I developed operational versions of Hirsch's H index that can be applied to each researcher's curriculum vitae (CV) to allow cross-disciplinary comparisons. The revised indices account for anomalies that potentially arise from tactical or opportunistic citation and publication behaviours by authors and editors, and can be calculated from readily available information. I split the original H index into nested indices to isolate networking activity, distinguish scientific production and productivity, and used nested Gini indices to identify intentional and successful inter-topical and inter-disciplinary research. I applied the most popular normalisations (i.e., per author and per year) using simple methodologies (i.e., least-squares linear and cubic interpolation fitting, whole-career vs. sub-periods, two-dimensional graphs) to solve empirical problems (e.g., sensitivity to citations, the "fashion" effect, attribution to disciplines, life cycle of articles) as well as open questions (e.g., the attribution of an article to a given discipline) associated with the original H index. I provided three numerical examples based on a representative heterodox, a representative orthodox multi-disciplinary, and a representative orthodox uni-disciplinary CV: the first CV includes 17 Scopus publications, and shows a highly heterodox (i.e., 5.8%), but no interdisciplinary research career, with a tiny networking component (i.e., 0.9%); the second CV includes 24 Scopus publications, and shows a slightly heterodox (i.e., 0.3%), but highly interdisciplinary (i.e., 53.9%) research career, with a small networking component (i.e., 14.3%); the third CV includes 16 Scopus publications, and shows slightly heterodox (i.e., 0.1%) and no interdisciplinary research career, with no networking component.

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Section: Introductionmentioning

confidence: 99%

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

Zagonari

2017

SSRN Journal

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“…Finally, I will not compare alternative datasets in terms of their reliability and stability [10,51]. Note that I will disregard individual characteristics that change over time, such as the researcher's age or position ( [2,3,52]), and individual characteristics that are fixed in time, such as gender or ethnicity [53][54][55]. In this paper, my interest is in indexes for, rather than determinants of, scientific activity [56].…”

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confidence: 99%

Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined

Zagonari

2019

Publications

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In this study, I developed operational versions of Gini’s and Hirsch’s indexes that can be applied to characterize each researcher’s publication history (PH) as heterodox, orthodox, and interdisciplinary. In addition, the new indicators warn against anomalies that potentially arise from tactical or opportunistic citation and publication behaviors by authors and editors, and can be calculated from readily available information. I split the original Hirsch index into nested indexes to isolate networking activity, as well as to distinguish scientific production (number of articles) from scientific productivity (rate of production), and used nested Gini indexes to identify intentional and successful intertopical and interdisciplinary research. I applied the most popular standardizations (i.e., per author and per year), and used simple methodologies (i.e., least-squares linear and cubic fitting, whole-career vs. subperiods, two-dimensional graphs). I provide three representative numerical examples based on an orthodox multidisciplinary PH, a heterodox PH from the social sciences, and an orthodox unidisciplinary PH from the physical sciences. Two additional numerical examples based on PHs from the life and health sciences show that the suggested PH characterization can be applied to different disciplines where different publication and citation practices prevail. Software is provided to help readers explore the use of these indicators.

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Career Levels and Their Effect on Scholarly Output and Impact of Women Scientists

Halevi

Bar‐Ilan

2018

Pub Res Q

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Gender, web presence and scientific productivity in nanoscience and nanotechnology

Cited by 5 publications

References 61 publications

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

Scientific Production and Productivity in Curriculum Vitae Characterisation: Simple and Nested H Indices that Support Cross-Disciplinary Comparisons

Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined

Career Levels and Their Effect on Scholarly Output and Impact of Women Scientists

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