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“Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al.

The overview of the study

The scholars analyzed mobility patterns of mobile devices to determine the movement of people in Houston, Texas after Hurricane Harvey hit it. The research aimed at developing a generalizable method that could predict people’s response and recovery after a natural disaster. It was found that the socioeconomic status and race of the affected people influenced their resilience capacity and patterns of evacuation.

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How the study fits with the current state of knowledge

The study seems to be consistent with other studies, although it takes a different methodology of data collection. For instance, while other studies retrieved data from the social media platforms such as Twitter, the researchers used large-scale smartphone geolocation data. The findings agree with other research works such as those conducted by Ilan and Rio (2018). Both works conclude that race and socioeconomic statuses affect people’s ability to cope with the impacts of natural disasters.

The type of study and data collection

The collected data is enough, however, the study methodology raises some concerns as the availability of the data used is restricted and not available to the public. It implies that other scholars may not easily access the data if they wanted to verify the results of this study. The authors appear to have accounted for the various factors that might have come into play. For instance, smoothing the time series data before clustering eliminated factors such as ping observation noises.

How the data supports the researchers’ story and conclusions

Data is used to support the conclusion of this study. For instance, in the study of mobility and movement patterns during Harvey, it was found that 68.1 percent of Houstonians stayed around while 31.9 percent left Houston to other cities and states (Hong et al., 2021). Those who stayed were people of low socioeconomic status and were impacted by the floods. These people were from distressed and abandoned areas of residence. Those who left were not affected by the storm and were people of higher socioeconomic statuses such as homeowners and those with high income. The results of the study are reliable as they are supported with reliable sources of data and concur with other studies.

References

Ilan, N., & Rio, Y. (2018). Economic vulnerability and resilience to natural hazards: a survey of concepts and measurements. Sustainability, 10(8), 2850. Web.

Hong, B., Bonczak, B., Gupta, A., & Kontokosta, C. (2021). Measuring inequality in community resilience to natural disasters using large-scale mobility data. Nature Communications, 12(1), 1-9. Web.

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StudyCorgi. (2022, August 2). “Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al. Retrieved from https://studycorgi.com/measuring-inequality-in-community-resilience-to-natural-disasters-by-hong-et-al/

Reference

StudyCorgi. (2022, August 2). “Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al. https://studycorgi.com/measuring-inequality-in-community-resilience-to-natural-disasters-by-hong-et-al/

Work Cited

"“Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al." StudyCorgi, 2 Aug. 2022, studycorgi.com/measuring-inequality-in-community-resilience-to-natural-disasters-by-hong-et-al/.

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StudyCorgi. "“Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al." August 2, 2022. https://studycorgi.com/measuring-inequality-in-community-resilience-to-natural-disasters-by-hong-et-al/.

References

StudyCorgi. 2022. "“Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al." August 2, 2022. https://studycorgi.com/measuring-inequality-in-community-resilience-to-natural-disasters-by-hong-et-al/.

References

StudyCorgi. (2022) '“Measuring Inequality in Community Resilience to Natural Disasters” by Hong et al'. 2 August.

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