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4 - Exploring the Suitability of Environmental Health Information for Parental Education Using Machine Learning Models

Published online by Cambridge University Press:  16 May 2025

Meng Ji
Affiliation:
University of Sydney
Michael Oakes
Affiliation:
University of Birmingham
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Summary

In this chapter, new computational models will focus on whether environmental health texts are suitable for parents rather than the general public. Logistic regression models will identify linguistic features that are important contributors to the prediction of the suitability of environmental health materials for parents and caregivers of young children, who are more likely to be affected by environmental health risks such as water pollution, excessive sun exposure, and radiation in natural and indoor environments.

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Chapter
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Multilingual Environmental Communications
Language Accessibility Matters
, pp. 75 - 103
Publisher: Cambridge University Press
Print publication year: 2025

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