Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year  in at least one of these indicators) and separately across 12 scientific fields. Correlation patterns vary across these 12 fields. In physics, total citations are highly negatively correlated with indicators of co-authorship adjustment and of author order, while in other sciences the negative correlation is seen only for total citation impact and citations to papers as single author. We propose a composite score that sums standardized values of these six log-transformed indicators. Of the 1,000 top-ranked scientists with the composite score, only 322 are in the top 1,000 based on total citations. Many Nobel laureates and other extremely influential scientists rank among the top-1,000 with the composite indicator, but would rank much lower based on total citations. Conversely, many of the top 1,000 authors on total citations have had no single/first/last-authored cited paper. More Nobel laureates of 2011-2015 are among the top authors when authors are ranked by the composite score than by total citations, H index, or Hm index; 40/47 of these laureates are among the top 30,000 by at least one of the six indicators. We also explore the sensitivity of indicators to self-citation and alphabetic ordering of authors in papers across different scientific fields. Multiple indicators and their composite may give a more comprehensive picture of impact, although no citation indicator, single or composite, can be expected to select all the best scientists.
Transdisciplinary (TD) approaches are increasingly used to address complex public health problems such as childhood obesity. Compared to traditional grant-funded scientific projects among established scientists, those designed around a TD, team-based approach yielded greater publication output after three to five years. However, little is known about how a TD focus throughout graduate school training may affect students' publication-related productivity, impact, and collaboration. The objective of this study was to compare the publication patterns of students in traditional versus TD doctoral training programs. Productivity, impact, and collaboration of peer-reviewed publications were compared between traditional (n = 25) and TD (n = 11) students during the first five years of the TD program. Statistical differences were determined by t-test or chi square test at p < 0.05. The publication rate for TD students was 5.2 ± 10.1 (n = 56) compared to 3.6 ± 4.5 per traditional student (n = 82). Publication impact indicators were significantly higher for TD students vs. traditional students: 5.7 times more citations in Google Scholar, 6.1 times more citations in Scopus, 1.3 times higher journal impact factors, and a 1.4 times higher journal h-index. Collaboration indicators showed that publications by TD students had significantly more co-authors (1.3 times), and significantly more disciplines represented among co-authors (1.3 times), but not significantly more organizations represented per publication compared to traditional students. In conclusion, compared to doctoral students in traditional programs, TD students published works that were accepted into higher impact journals, were more frequently cited, and had more cross-disciplinary collaborations.
How to quantify the impact of a researcher’s or an institution’s body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. Here, we pursue a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as “very high research activity”. Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.
Systematic reviews are important for informing clinical practice and health policy. The aim of this study was to examine the bibliometrics of systematic reviews and to determine the amount of variance in citations predicted by the journal impact factor (JIF) alone and combined with several other characteristics.
The h index bibliometric indicator for evaluating scientists and scientific institutions plays an increasingly important role in evaluating contemporary scientific research, including chemistry.
- Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
- Published over 6 years ago
This article provides a broad overview of widely available measures of academic productivity and impact using publication data and highlights uses of these metrics for various purposes. Metrics based on publication data include measures such as number of publications, number of citations, the journal impact factor score, and the h-index, as well as emerging metrics based on document-level metrics. Publication metrics can be used for a variety of purposes for tenure and promotion, grant applications and renewal reports, benchmarking, recruiting efforts, and administrative purposes for departmental or university performance reports. The authors also highlight practical applications of measuring and reporting academic productivity and impact to emphasize and promote individual investigators, grant applications, or department output.
The impact factor (IF) of scientific journals has acquired a major role in the evaluations of the output of scholars, departments and whole institutions. Typically papers appearing in journals with large values of the IF receive a high weight in such evaluations. However, at the end of the day one is interested in assessing the impact of individuals, rather than papers. Here we introduce Author Impact Factor (AIF), which is the extension of the IF to authors. The AIF of an author A in year t is the average number of citations given by papers published in year t to papers published by A in a period of Δt years before year t. Due to its intrinsic dynamic character, AIF is capable to capture trends and variations of the impact of the scientific output of scholars in time, unlike the h-index, which is a growing measure taking into account the whole career path.
The decision about which journal to choose for the publication of research deserves further investigation.
The Hirsch index (h-index) is a measure that evaluates both research volume and quality-taking into consideration both publications and citations of a single author. No prior work has evaluated academic productivity and contributions to the literature of adult total joint replacement surgeons. This study uses h-index to benchmark the academic impact and identify characteristics associated with productivity of faculty members at joint replacement fellowships.
To evaluate the relative research productivity and ranking of anesthesiology departments in Canada and the United States, using the Hirsch index (h-index) and 4 other previously validated metrics.