Tue, Aug 03, 2021:On Demand
Background/Question/Methods
It was 2007. We were the first generation of UNAM undergrad students, mostly women, to undertake our “social service” (480 hrs of work community service related to our career) on conservation projects at the Lacandona Jungle, in Southeast Mexico. Our work was based in low-income rural communities, where gender roles were strong, and where land owners (“ejidatarios”) involved in decision-making were male. Fast forward to 2015. I had just finished my PhD and come back to Mexico on the onset of genomic data being widespread available for non-model organisms, and thus for molecular ecology. I started teaching a CONABIO-UNAM course on bioinformatics for ecology and evolution postgraduate students. Gender stereotypes dictate that programing is easier for men, so I worked to prevent those ideas from permeating my class. Today, I am leading a transdisciplinary project on applying evolutionary research to forest conservation, which includes co-generating data with a periurban rural community where few women are involved in the management of their forest.
Here I will summarize how we dealt with each situation and how (if) it influenced the future of the projects and people involved. To do so I will narrate our empirical experience including the actions and decisions that our teacher toke during my social service, and what I have learned as a student, first time lecturer and project leader. I will present data on the projects development, how my students perceived and perceive bioinformatics before and after the course, and the results of including women in a participatory monitoring of forest health.
Results/Conclusions I will discuss lessons learned, including how data and male allies can help, why it really helps putting our money and time where our mouth is, and why we need to include all women and not only those who already have privileges. I will conclude highlighting the lessons that I am still learning how to learn, and summarizing how we can apply the (real) scientific method to achieve gender equality in Ecology.
Results/Conclusions I will discuss lessons learned, including how data and male allies can help, why it really helps putting our money and time where our mouth is, and why we need to include all women and not only those who already have privileges. I will conclude highlighting the lessons that I am still learning how to learn, and summarizing how we can apply the (real) scientific method to achieve gender equality in Ecology.