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Lauren Marr

Lauren Marr

Ph.D. researcher with 10 years of experience
Oceanside, San Diego

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About Lauren Marr:

Lauren Crossland-Marr is a cultural anthropologist who has experience researching, writing, and teaching on topics of technology, science, economy, and food systems. In May 2020, she received her PhD from Washington University in St. Louis. Currently, she is a post-doctoral researcher on an EU-funded project that explores public awareness and acceptance of new biotechnology applications in agriculture. From 2017 to 2018, she conducted participant-observation on the halal certification industry in Milan, Italy to determine the impact of local cultural foodways on certifications meant for global markets. In 2014, Lauren received an MA in anthropology from the Catholic University of America. In 2007, she received her bachelor’s degree in anthropology and Italian language from the University of Maryland, College Park.

Experience

As a cultural anthropologist, I have spent the last decade conducting research projects across several topics including technology, environment and health, and the global economy. I am a skilled and confident researcher who has spent the last decade communicating scientific research to diverse audiences. 

Education

I successfully defended my dissertation in May 2020. For my dissertation fieldwork, I conducted surveys, contextual inquiry/participant-observation, interviews, and focus groups to answer my research question: how do people ethically participate in the global food system? Through my research with Muslim communities building halal certifications, I became well-versed in understanding the global food system from production to consumption. I performed contextual inquiry, spending time on farms, in production sites, and at offices. Through surveys and a focus group, I also investigated how consumers understood halal, showing that there is a huge amount of trust when evaluating foods labelled with any certification (organic, Fair Trade, etc.) and halal certification is no exception. To analyze the data collected, I used NVIVO, and I am well-versed in it, and similar software.

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