Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/5042
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dc.contributor.authorAlan Lee-
dc.date.accessioned2024-01-11T21:58:12Z-
dc.date.available2024-01-11T21:58:12Z-
dc.date.issued2024-01-11-
dc.identifier.citationPublished--Unlimited Distributionen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/5042-
dc.descriptionHuman Resources / Graduate Student Researchen_US
dc.description.abstractTo combat food insecurity, the Department of the Navy will increase the Basic Needs Allowance (BNA) total household income requirement up to 150% of the Federal Poverty Guideline (FPG) in accordance with the National Defense Authorization Act of 2023. This thesis uses machine learning techniques on comparable civilian data to create a model that best predicts the risk of food insecurity and the characteristics of Sailors who are food insecure. To measure the effectiveness of the BNA, this study simulates the increase in total household income up to 130% and 150% FPG, with and without the Basic Allowance for Housing included in the total household income calculation and reruns the prediction model to see the changes in predicted risk of food insecurity. The model suggests that 17.6% of Sailors are food insecure. Additionally, the BNA in each simulation insignificantly decreases the food insecurity rate. Less than 1% of Sailors qualify for the BNA, while 17% are predicted to be food insecure. Therefore, the BNA provides an insufficienen_US
dc.description.sponsorshipAcquisition Research Programen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesHuman Resources;NPS-HR-23-255-
dc.subjectFood Insecurityen_US
dc.subjectBasic Needs Allowanceen_US
dc.subjectBNAen_US
dc.titleCombating Food Insecurity in the U.S. Navyen_US
dc.typeThesisen_US
Appears in Collections:NPS Graduate Student Theses & Reports

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