Search results

Extends the transactional‐transformational model of leadership by deductively developing four theoretical behavioral types of leadership based on a historical analysis of leadership literature. Then, in an exploratory empirical phase, uses two data sets to inductively develop alternative models of leadership types. Finally, with a third data set, tests several theoretically plausible typologies using second‐order confirmatory factor analysis (CFA). The results of the CFA generally support the existence of four leadership types: directive leadership, transactional leadership, transformational leadership, and empowering leadership.

This paper aims to document the proliferating range of alternatives to the impact factor that have arisen within the past five years, coincident with the increased prominence of open access publishing.

This paper offers an overview of the history of the impact factor as: a measure for scholarly merit; a summary of frequent criticisms of the impact factor's calculation and usage; and a framework for understanding some of the leading alternatives to the impact factor.

This paper identifies five categories of alternatives to the impact factor: measures that build upon the same data that informs the impact factor; measures that refine impact factor data with “page rank” indices that weight electronic resources or web sites through the number of resources that link to them; measures of article downloads and other usage factors; recommender systems, in which individual scholars rate the value of articles and a group's evaluations pool together collectively; and ambitious measures that attempt to encompass the interactions and influence of all inputs in the scholarly communications system.

Librarians can utilize the measures described in this paper to support more robust collection development than is possible through reliance on the impact factor alone.

The following bibliography focuses mainly on programs which can run on IBM microcomputers and compatibles under the operating system PC DOS/MS DOS, and which can be used in online information and documentation work. They fall into the following categories:

A few hours before the May 17, 2004 gala to commemorate the legal decision that ended “separate but equal” facilities for black and white U.S. citizens, comedian Bill Cosby heard a radio broadcast that was on his wavelength. As Cosby listened to “Ask the Chief” on May 17, 2004 Washington, DC Police Chief Charles H. Ramsey recounted the number of children who had been the victims of homicide (Schroeder, 2004). A few hours later, Cosby picked up on the discussion with a live audience at Constitution Hall to celebrate the historic verdict of Brown v. Board of Education of Topeka, Kansas. During the event, the National Association for the Advancement of Colored People, the Legal Defense and Education Fund, and Howard University acknowledged Cosby for his multimillion dollar contributions to historically black colleges and universities.

Synergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.

The synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.

The findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.

In a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.