Abstract
A 2011 Foresight report by the UK Government Office for Science introduced and raised questions and concerns about trapped populations. Conceptualized as consisting of actors who are highly vulnerable to climate and environmental stressors given limited resources (economic, social), trapped populations lack the capacity to adapt to these stressors in situ or by choosing to migrate. Informed by insights and omissions from this report and subsequent theoretical and empirical research, we propose a guiding operational definition and corresponding set of five empirical steps to identify and study trapped populations. In an empirical demonstration using data from the Mexican Family Life Survey (MxFLS), we detail these five steps, which permit both retrospective and prospective identification of trapped populations via predicted probabilities derived from statistical models. We find that our approach performs well. For example, using model coefficients estimated from the first wave of the MxFLS and actors’ characteristics from the second wave of the MxFLS to predict the probability of non-migration in the latter wave, we find that our approach overwhelmingly identifies observed non-migrants. We conclude with the observation that our approach, as well as other potential approaches, can and should continue to be refined to ensure theoretical and empirical integration, consistency, and cooperation in studying and understanding trapped populations and human [im]mobility more broadly.
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Data availability
The analyses in this paper were performed using secondary data as described in the “Empirically identifying trapped populations” section.
Notes
Migrations that took place in 2003 are sourced from the 2005 MxFLS-2 survey, while migrations that took place prior to 2003are sourced from the 2002 MxFLS-1. Migration modules in both surveys collect information about current (ongoing) and retrospective (recent) migrations of less than a year (temporary, according to the MxFLS) longer (permanent, according to the MxFLS).
Moves to a different community within the same municipality were coded as migrations, while moves within communities were not.
Specifically, we coded survey respondents as employed if they reported a primary, secondary, etc. job. If the respondent did not report any job, we coded them as unemployed, regardless of whether they were ever previously employed or were searching for employment.
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Acknowledgements
The authors of this paper are listed alphabetically by last name. This work is supported by center grants #P2CHD041023 and #2P2CHD06661311 awarded to the Minnesota Population Center at the University of Minnesota and the CU Population Center (CUPU) in the Institute of Behavioral Science at the University of Colorado Boulder, respectively, by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. This work is also supported by Grant No. 1416860 from the National Science Foundation, and benefited from the CUPC Conference on Climate Change, Migration and Health (NICHD project 5R13HD078101), specifically, the installment held at the University of Colorado Boulder on May 17–18, 2018, with support from the International Union for the Scientific Study of Population. Earlier versions of this paper were presented at the workshop, Demographic Responses to Changes in the Natural Environment, at the University of Wisconsin-Madison on October 24, 2019, the conference, Environmental Non-migration: Frameworks, Methods and Cases, at the Technische Universität in Dresden on June 20, 2019, and at the annual meetings of the Population Association of America in Austin, TX, on April 11, 2019, and the American Association of Geographers in Washington, D.C., on April 4, 2019. The authors wish to thank members of the above audiences for their helpful comments, as well as Jenna Nobles for her support of Esteban J. Quiñones in securing and preparing the MxFLS data.
Funding
Eunice Kennedy Shriver National Institute of Child Health and Human Development,P2CHD041023,2P2CHD06661311,5R13HD078101,Jack DeWaard,National Science Foundation (US),1416860
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DeWaard, J., Hunter, L.M., Mathews, M.C. et al. Operationalizing and empirically identifying populations trapped in place by climate and environmental stressors in Mexico. Reg Environ Change 22, 29 (2022). https://doi.org/10.1007/s10113-022-01882-7
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DOI: https://doi.org/10.1007/s10113-022-01882-7