Unveiling scholarly insights: A bibliometric analysis of literature on gender bias at the workplace
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.45Keywords:
Gender bias, Gender discrimination, Bibliometric analysis, Systematic literature review, Data visualization.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Gender bias and discrimination in the workplace remain significant global challenges, impacting individuals and organizations. Despite heightened awareness and scholarly focus, a comprehensive, up-to-date evaluation of the literature’s scientific impact and citation trends is missing. This research article addresses this gap through a bibliometric analysis from 2000 to 2023, assessing gender bias’s scientific significance, citations, and pre-publication information. Utilizing tools like RStudio, VOS viewer, Dimensions analytics, and MS Excel, the study analyzes manuscripts from the Dimensions database. The analysis reveals notable trends, showing a steady rise in publications from 2003, with fluctuations in 2002 and 2008-2011, stability from 2012-2015, and a significant surge from 2016-2023, peaking in 2019-2022. The United States leads in publication quantity and collaboration. Key topics such as "Economics and Identity," the "glass cliff phenomenon," and the "climate for women in academic science" dominate citations. Prominent journals like "Building A New Leadership Ladder" and "Plos One" highlight the interdisciplinary nature of gender bias research. Influential contributors like Geffner CJ, Kim S, and Ryan MK are acknowledged for their dedication. This study underscores the interdisciplinary reach of gender bias research across Human Society, Commerce, Law, Biomedical Sciences, and Psychology, offering valuable insights into publication trends, collaborative networks, and thematic developments. The findings emphasize the need for continued exploration and collaboration to address gender-related challenges in professional settings.Abstract
How to Cite
Downloads
Similar Articles
- Anvar Mavlonov , Saidamir Saidov , Jakhongir Mirsultanov, Rano Boboeva , The Features of bone destruction in rabbits with experimental metabolic syndrome , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- K Sreenivasulu, Sameer Yadav, G Pushpalatha, R Sethumadhavan, Anup Ingle, Romala Vijaya, Investigating environmental sustainability applications using advanced monitoring systems , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- P. Susai Raj, A. Edward William Benjamin, Evaluating the effectiveness of academic resilience intervention for at-risk students at higher secondary level , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Prince Williams, Nilesh M. Patil, Allanki S. Rao, Chandra M. V. S. Akana, K. Soujanya, Aakansha M. Steele, Transformative effects of connectivity technologies on urban infrastructure and services in smart cities , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- K. Akila, Location-specific trusted third-party authentication model for environment monitoring using internet of things and an enhancement of quality of service , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- R.R. Jenifer, V.S.J. Prakash, Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Vikas Jangra, Dr. Vikas Jangra, Vandana, Comparative study of color difference on coated and uncoated paper in digital printing , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Deepak K. Sharma, Vandana ., Pankaj Kumar, Ambrish Pandey, Jitender Pal, Investigating physico-chemical characteristics of water and wastewater in the printing industry , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- G. C. Sowparnika, D. A. Vijula, Modeling and control of boiler in thermal power plant using model reference adaptive control , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Gomathi Ramalingam, Logeswari S, M. D. Kumar, Manjula Prabakaran, Neerav Nishant, Syed A. Ahmed, Machine learning classifiers to predict the quality of semantic web queries , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
<< < 44 45 46 47 48 49 50 51 52 53 > >>
You may also start an advanced similarity search for this article.

