To put in place inclusive strategies that increase the resilience of women and men in all their diversity, there is an urgent need to better understand the gendered effects of climate change across countries. To achieve this, this paper explores the connections between phenomena related to climate change and gender related outcomes in Bangladesh, Cambodia, Nepal, the Philippines and Timor-Leste. In particular, it tests these associations by utilizing random forest machine learning techniques and binary logistic regression analysis, on a data set that integrates data from Demographic and Health Surveys (DHS) and geographical information systems (GIS). The paper concludes that climate change is having profound and unequal impacts on women and girls, particularly those who are vulnerable and depend on natural resources. By examining the evidence, we can gain a better understanding of the complex relationship between climate change and gender. From changes in rainfall patterns to increased aridity and high temperatures, it is critical to identify and address these challenges with a gender lens. Having this evidence is the first step, but it is up to us all to use it to guide our actions towards solutions grounded in facts and tailored to the specific needs of those most affected.
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