This presentation seeks to explore the potential role of gender-disaggregated call detail records (CDR’s) in studying vulnerability to climate change. Climate change is a dire issue as it has detrimental ramifications for human development. Although the exact effects differ depending on location, it generally has adverse effects on human health and even socioeconomic well-being (1, 7). In this day and age, we have phenomenal disaster forecasting abilities thanks to the GRACE and GRACE-Fo satellite programs as well as the use of machine learning and AI with our current climate models (5, 9). However, in order for these forecasts to be useful, we have to know who is most vulnerable and make sure they receive appropriate warnings and aid. CDR’s provide data about population dynamics at a high spatial and temporal resolution, making them a great tool for knowing the population distribution and which people are located in the most vulnerable areas (3). When Csáji et al. regressed CDR data with independent statistics, they found a correlation of 0.92, validating it as a means of determining population dynamics (2). By combining CDR’s with our forecasting and tracking abilities, we have an amazing capacity to adapt to climate disasters, allowing us to improve the safety and well-being of our society.
However, up until recently, gender differences have barely been considered when addressing climate vulnerability (6). The fact of the matter is that men and women across many different cultures face distinct climate-related vulnerabilities that need to be addressed individually (8). Unfortunately, progress in addressing gender disparities in climate vulnerability has been stifled by misconceptions and generalizations, which plague much of today’s literature (6). Dujardin et al. did not account for gender when describing CDR’s (2) Despite these setbacks, there is still hope for attaining greater gender equality in climate change vulnerability studies. It has recently been shown by Goel et al. that CDR’s can be used to evaluate the dynamics of men and women separately (4). I intend to use these gender-disaggregated CDR’s for the purpose of assessing climate change vulnerability. That way, we could observe the gender distribution among vulnerable groups of people, enabling us to allocate aid specific to the gender proportions. Not only would this enhance the well-being of everybody, but would also help mitigate gender inequality in terms of suffering from climate disasters.