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Hindi Research Article, J Clin Exp Oncol Vol: 4 Issue: 3
Developing Research Networks to Enhance Cross-Mentoring and Representation of Women in Clinical and Experimental Oncology
| Gillian Bowser1,2, Katherine Wilkins3, Ulrike Gretzel4, Elizabeth Davis5 and Mark A. Brown2,6-8* | |
| 1Natural Resource Ecology Laboratory, Colorado State University, USA | |
| 2Department of Ethnic Studies, Colorado State University, USA | |
| 3Graduate Degree Program in Ecology, Colorado State University, USA | |
| 4School of Business, University of Queensland, Brisbane, Australia | |
| 5School of Management, University of San Francisco, USA | |
| 6Department of Clinical Sciences, Colorado State University, USA | |
| 7Cell and Molecular Biology Program, Colorado State University, USA | |
| 8Colorado School of Public Health, Colorado State University, USA | |
| Corresponding author : Mark A Brown 801 Oval Drive, Campus Code 1052, Fort Collins, CO 80523-1052, USA Tel: (970) 491-5782 E-mail: M.Brown@colostate.edu |
|
| Received: July 03, 2015 Accepted: August 24, 2015 Published: August 27, 2015 | |
| Citation: Brown MA, Bowser G, Wilkins K, Gretzel U, Davis E, (2015) Developing Research Networks to Enhance Cross-Mentoring and Representation of Women in Clinical and Experimental Oncology. J Clin Exp Oncol 4:3. doi:10.4172/2324-9110.1000142 |
Abstract
Developing Research Networks to Enhance Cross-Mentoring and Representation of Women in Clinical and Experimental Oncology
Mentoring the next generation of oncology researchers is essential for ensuring the development of 21st century cancer therapeutics. The failure of universities and research centers to recruit and retain women in the technological disciplines supporting experimental oncology represents a major limitation in the sustainability of the current pipeline for translational oncology. The Global Women Scholars Network recently launched an initiative to implement and evaluate a social recommender system to enhance crossmentoring of women in the sciences. In doing so, we explore the untested hypothesis that social network recommender systems are an effective way to address the lingering gap between women and men in the sciences.
