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Kelsea Best

Kelsea Best

· Assistant Professor, Civil Environmental and Geodetic Engineering

Ohio State University · Architecture

Active 2018–2024

h-index7
Citations187
Papers2422 last 5y
Funding
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About

Dr. Kelsea Best is an Assistant Professor in the Department of Civil, Environmental, and Geodetic Engineering and the City and Regional Planning program at Ohio State University. Her research focuses on understanding how climate change interacts with human societies and infrastructure, exploring how people may adapt to climate change effects, and designing and implementing climate adaptation measures in a just and equitable manner. Her work is highly interdisciplinary, connecting methods, disciplines, and researchers across various geographies and fields. Her research is grounded in data-driven methods, including machine learning and agent-based modeling, while also seeking to advance conventional modeling approaches by incorporating personal narratives and community participation to inform computational models. Some of her current projects involve modeling individual and household migration decisions under climate change, assessing renters’ vulnerability to natural disasters and implications for housing security, identifying infrastructure needs for climate-migrant-receiving communities, and understanding the dynamics of climate gentrification in coastal cities.

Research topics

  • Sociology
  • Computer Science
  • Ecology
  • Machine Learning
  • Geography
  • Psychology
  • Artificial Intelligence
  • Biology
  • Economics
  • Environmental planning
  • Socioeconomics
  • Demography
  • Mathematics
  • Econometrics
  • Statistics
  • Demographic economics

Selected publications

  • The risks of invisibilization of populations and places in environment-migration research

    Humanities and Social Sciences Communications · 2021 · 34 citations

    • Sociology
    • Computer Science
    • Environmental planning

    Abstract Recent years have seen an increase in the use of secondary data in climate adaptation research. While these valuable datasets have proven to be powerful tools for studying the relationships between people and their environment, they also introduce unique oversights and forms of invisibility, which have the potential to become endemic in the climate adaptation literature. This is especially dangerous as it has the potential to introduce a double exposure where the individuals and groups most likely to be invisible to climate adaptation research using secondary datasets are also the most vulnerable to climate change. Building on significant literature on invisibility in survey data focused on hard-to-reach and under-sampled populations, we expand the idea of invisibility to all stages of the research process. We argue that invisibility goes beyond a need for more data. The production of invisibility is an active process in which vulnerable individuals and their experiences are made invisible during distinct phases of the research process and constitutes an injustice. We draw on examples from the specific subfield of environmental change and migration to show how projects using secondary data can produce novel forms of invisibility at each step of the project conception, design, and execution. In doing so, we hope to provide a framework for writing people, groups, and communities back into projects that use secondary data and help researchers and policymakers incorporate individuals into more equitable climate planning scenarios that “leave no one behind.”

  • Extreme weather and marriage among girls and women in Bangladesh

    Global Environmental Change · 2020 · 61 citations

    • Sociology
    • Demographic economics
    • Demography
  • Random forest analysis of two household surveys can identify important predictors of migration in Bangladesh

    Journal of Computational Social Science · 2020 · 39 citations

    1st authorCorresponding
    • Machine Learning
    • Computer Science
    • Artificial Intelligence

Frequent coauthors

Education

  • PhD, Earth and Environmental Science

    Vanderbilt University

    2022
  • BSE, Chemical Engineering

    Princeton University

    2015

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