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.”
Highlights
Research and knowledge production can be affected by biases and contain the risk of being part of theproduction of inequality
We provide some suggestions as to how researchers may interrogate their own research across the stages of production to attempt to prevent unintentional invisibility in the hope that environmentmigration researchers begin to carefully consider invisibility across all stages of research
Addressing calls focusing on equity in climate policy requires a more thorough understanding of when and how vulnerable people are made invisible by the academic knowledge production of population environment research. To highlight this process of exclusion during the modus operandi of academic knowledge production, we suggest using a conceptual framework that illustrates the stages of the research process in which invisibility may be introduced (Fig. 1)
Summary
Research and knowledge production can be affected by biases and contain the risk of being part of the (re)production of inequality. The use of secondary data (census data, DHS-type survey data[1] or data from observatories or monitoring sites such as HDSS[2], for population data...), and their combination with available environmental data (such as land use data classified from satellite images, weather station data, etc.) making it possible to produce research at a speed, scale, and cost that cannot be equalled (https:// terra.ipums.org/home) Despite this progress, few large-sample studies have examined the evolution and transformation of migration systems under changing environmental conditions, due to the remaining difficulties involved in capturing the dynamic components of both dimensions (with HDSS data: Call et al, 2017; Hunter et al, 2017; Hunter et al, 2014; Lalou et al, 2019; with Terra Populus data: Nawrotzki et al, 2016, 2017); with DHS data: Hallegatte and Rozenberg, 2017). The conceptual framework (Fig. 1) highlights five scales at which invisibility may be introduced or reinforced in the research process, focusing on research that depends on the use of secondary data
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