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  • Item type:Publication,
    Gender disparities in gastroenterology and hepatology conferences: The journey towards equality Open PDF 
    (Springer Science and Business Media LLC, 2024-06-27)
    Devi, Jalpa
    ;
    Butt, Amna Subhan
    ;
    Rai, Lajpat
    ;
    Kumar, Jatin
    ;
    Memon, Sadik
    Background: This study scrutinizes gender representation in invited faculty and conference committee leadership at key gastroenterology and hepatology conferences in Pakistan over five years, exploring the impact of the "glass ceiling" and "sticky floor" phenomena on gender diversity within academic medicine. Methods: This cross-sectional study was conducted between January and March of 2023. The three major national societies of gastroenterology and hepatology in Pakistan that had been established for more than 10 years and the scientific programs of their annual conferences, which were publicly accessible, were included and coded as Society 1, Society 2 and Society 3 to maintain anonymity. The scientific programs for the last five years (2018-2022) were retrieved. The roles of invited faculties were identified as invited speakers, moderators, chairs/panelists, presidents and chairs of organizing or scientific committees and the gender makeup of the faculty was compared. Regression analysis was used to evaluate the trends for female representation over time for each role. Results: Significant gender disparity was evident by an extremely lower cumulative proportion of female invited faculty compared to males (211 [11.9%] vs. 1567 [88.1%], p 0.001). The predominance of invited male faculty was observed across all societies as well as in various roles of invited faculty (p 0.01). A significant disparity has also been observed in leadership positions of all three societies (43 [95.5%] males vs. 2 [4.5%] females, p 0.001), while the trend of women's underrepresentation across all societies remained almost unchanged over time (slope = 0.08, R2 = - 0.078, p-value = 0.875). Conclusion: Our study unveils striking gender disparities in women's representation as invited speakers and other roles at the annual scientific conferences of major gastroenterology and hepatology. Additionally, male dominance remains entrenched, notably in leadership positions, necessitating a proactive, multifaceted approach to rectify gender inequities.
  • Item type:Publication,
    Meeting the challenge of gender inequality through gender transformative research: lessons from research in Africa, Asia, and Latin America Open PDF 
    (Routledge, 2023)
    Njuki, J.
    ;
    Melesse, M.
    ;
    Sinha, C.
    ;
    Seward, R.
    ;
    Renaud, M.
    While the global development agenda has prioritized gender equality, many challenges remain, and the COVID-19 crisis has exacerbated inequalities. Gender transformative approaches to social change have the potential to address the underlying causes of inequality. This paper draws insights from studies funded by Canada's International Development Research Centre to understand how integrating gender transformative approaches to research can support social change. The findings suggest that gender transformative research is most successful in supporting change when it analyzes and addresses the multiple causes of inequality, takes an intersectional and structural approach, embeds the research in local contexts, and engages power holders and perpetrators of inequality. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
  • Item type:Publication,
    Advance Gender Prediction Tool of First Names and its Use in Analysing Gender Disparity in Computer Science in the UK, Malaysia and China
    (Institute of Electrical and Electronics Engineers Inc., 2018)
    Zhao, H.
    ;
    Kamareddine, F.
    Global gender disparity in science is an unsolved problem. Predicting gender has an important role in analysing the gender gap through online data. We study this problem within the UK, Malaysia and China. We enhance the accuracy of an existing gender prediction tools of names that can predict the sex of Chinese characters and English characters simultaneously and with more precision. During our research, we found that there is no free gender forecasting tool to predict an arbitrary number of names. We addressed this shortcoming by providing a tool that can predict an arbitrary number of names with free requests. We demonstrate our tool through a number of experimental results. We show that this tool is better than other gender prediction tools of names for analysing social problems with big data. In our approach, lists of data can be dynamically processed and the results of the data can be displayed with a dynamic graph. We present experiments of using this tool to analyse the gender disparity in computer science in the UK, Malaysia and China. © 2017 IEEE.