Does a long reference list guarantee more citations? Analysis of Malaysian highly cited and review pPapers

Earlier publications have shown that the number of references as well as the number of received citations are field-dependent. Consequently, a long reference list may lead to more citations. The purpose of this article is to study the concrete relationship between number of references and citation counts. This article tries to find an answer for the concrete case of Malaysian highly cited papers and Malaysian review papers. Malaysian paper is a paper with at least one Malaysian affiliation. A total of 2466 papers consisting of two sets, namely 1966 review papers and 500 highly-cited articles, are studied. The statistical analysis shows that an increase in the number of references leads to a slight increase in the number of citations. Yet, this increase is not statistically significant. Therefore, a researcher should not try to increase the number of received citations by artificially increasing the number of references

Self-citation and corruption: cross-sectional, cross-country study

# Background Self-citation appears to be widely prevalent. However, the structural drivers of self-citation are poorly understood. # Methods Data for this study were obtained from a recently published study of Scopus data aggregated across all authors with \>5 publications, across all scientific fields, which yielded aggregate, country-level data on the mean co-author self-citation rate for the period 1960-2018. These data were merged with 2018 data from Transparency International on corruption, and additional data extracted from the World Development Indicators. The country-level association between the self-citation rate and the corruption index was estimated using multivariable linear regression. # Results Across 178 countries, the correlation between the mean self-citation rate and the corruption index was -0.52, 95% confidence interval, CI=-0.62 to -0.41. Among the 49 countries in the lowest quartile of the corruption index, the mean self-citation rate was 0.24 (standard deviation, SD=0.06). Among the 44 countries in the highest quartile of the corruption index, the mean self-citation rate was 0.21 (SD=0.05). In a weighted linear regression model with robust estimates of variance, the corruption index had a statistically significant association with the mean self-citation rate (2nd quartile compared with 1st quartile: *b*=-0.08 (95% CI=-0.17 to -0.01); 3rd quartile: *b*=-0.11 (95% CI=-0.19 to -0.02); 4th quartile: *b*=-0.10 (95% CI=-0.19 to -0.01; N=165). The implied effect size was large in magnitude and robust to potential confounding by unmeasured covariates. # Conclusions In this cross-sectional, cross-country analysis, there was a strong correlation between a country’s overall level of corruption and the mean self-citation rate. The estimated association was statistically significant, large in magnitude, and unlikely to be explained away by unmeasured confounding. Better understanding of how corruption norms evolve is likely to be critical in addressing the problem of extreme self-citation and other forms of citation manipulation

Considerations on the Impact Factor as a Tool in Scientific Assessment

This exploratory study aims to wide the debate over the impact factor and its application as a tool in the assessment of science. The analysis of scientific activity has been the subject of much debate, especially in the last decade. The impact factor and the citation frequency have been regularly used in the individual analysis of researchers as well verify the performance of journals, investigators, research centers, graduate programs, institutions and countries. The impact factor of a journal can be highly influenced by few of its articles that are very frequently cited. Some researchers are more concerned about publishing in high impact journals than about doing science itself. The manner how the scientific research output is assessed by funding agencies, academic institutions, among others, has been the subject of much debate and the current great question is whether the impact factor (IF) is the best indicator to assess the scientific quality or an already obsolete measure. There is one movement of researchers against the impact factor to be used as a qualitative measure of research articles or even as an indicator of the contribution of a scientist for possible hiring, promotion or decision for grant. Then, there is a need of academic community deeply reflect on this important issue

White Paper: Measuring Research Outputs Through Bibliometrics

The suggested citation for this white paper is: University of Waterloo Working Group on Bibliometrics, Winter 2016. White Paper: Measuring Research Outputs through Bibliometrics, Waterloo, Ontario: University of Waterloo.This White Paper provides a high-level review of issues relevant to understanding bibliometrics, and practical recommendations for how to appropriately use these measures. This is not a policy paper; instead, it defines and summarizes evidence that addresses appropriate use of bibliometric analysis at the University of Waterloo. Issues identified and recommendations will generally apply to other academic institutions. Understanding the types of bibliometric measures and their limitations makes it possible to identify both appropriate uses and crucial limitations of bibliometric analysis. Recommendations offered at the end of this paper provide a range of opportunities for how researchers and administrators at Waterloo and beyond can integrate bibliometric analysis into their practice

Systematic Analysis of the Factors Contributing to the Variation and Change of the Microbiome

abstract: Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications, citations, funding, collaborations, and other explanatory variables or contextual factors. What is observed in the microbiome, or any historical evolution of a scientific field or scientific knowledge, is that these changes are related to changes in knowledge, but what is not understood is how to measure and track changes in knowledge. This investigation highlights how contextual factors from the language and social context of the microbiome are related to changes in the usage, meaning, and scientific knowledge on the microbiome. Two interconnected studies integrating qualitative and quantitative evidence examine the variation and change of the microbiome evidence are presented. First, the concepts microbiome, metagenome, and metabolome are compared to determine the boundaries of the microbiome concept in relation to other concepts where the conceptual boundaries have been cited as overlapping. A collection of publications for each concept or corpus is presented, with a focus on how to create, collect, curate, and analyze large data collections. This study concludes with suggestions on how to analyze biomedical concepts using a hybrid approach that combines results from the larger language context and individual words. Second, the results of a systematic review that describes the variation and change of microbiome research, funding, and knowledge are examined. A corpus of approximately 28,000 articles on the microbiome are characterized, and a spectrum of microbiome interpretations are suggested based on differences related to context. The collective results suggest the microbiome is a separate concept from the metagenome and metabolome, and the variation and change to the microbiome concept was influenced by contextual factors. These results provide insight into how concepts with extensive resources behave within biomedicine and suggest the microbiome is possibly representative of conceptual change or a preview of new dynamics within science that are expected in the future.Dissertation/ThesisDoctoral Dissertation Biology 201

Congress UPV Proceedings of the 21ST International Conference on Science and Technology Indicators

This is the book of proceedings of the 21st Science and Technology Indicators Conference that took place in València (Spain) from 14th to 16th of September 2016. The conference theme for this year, ‘Peripheries, frontiers and beyond’ aimed to study the development and use of Science, Technology and Innovation indicators in spaces that have not been the focus of current indicator development, for example, in the Global South, or the Social Sciences and Humanities. The exploration to the margins and beyond proposed by the theme has brought to the STI Conference an interesting array of new contributors from a variety of fields and geographies. This year’s conference had a record 382 registered participants from 40 different countries, including 23 European, 9 American, 4 Asia-Pacific, 4 Africa and Near East. About 26% of participants came from outside of Europe. There were also many participants (17%) from organisations outside academia including governments (8%), businesses (5%), foundations (2%) and international organisations (2%). This is particularly important in a field that is practice-oriented. The chapters of the proceedings attest to the breadth of issues discussed. Infrastructure, benchmarking and use of innovation indicators, societal impact and mission oriented-research, mobility and careers, social sciences and the humanities, participation and culture, gender, and altmetrics, among others. We hope that the diversity of this Conference has fostered productive dialogues and synergistic ideas and made a contribution, small as it may be, to the development and use of indicators that, being more inclusive, will foster a more inclusive and fair world