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dc.contributor.advisorLin-Greenberg, Erik
dc.contributor.authorRippy, Julian T.
dc.date.accessioned2023-01-19T18:39:03Z
dc.date.available2023-01-19T18:39:03Z
dc.date.issued2022-09
dc.date.submitted2022-10-20T14:26:07.688Z
dc.identifier.urihttps://hdl.handle.net/1721.1/147231
dc.description.abstractThis thesis presents a new method for estimating force size and composition for Military Operations Other than War. While military planners have tools for planning these kinds of operations, they are largely inaccessible or unsuitable for civilian use. The most common tool for force estimation in MOOTW, force ratios, is inaccurate and based on questionable assumptions. The new method presented here, operational inference, is a mixed-methods approach which uses a multivariate distance measure in order to determine which military operations are similar to each other. Using this information, a researcher can identify similar cases for focused comparison, allowing for both qualitative and quantitative improvements in force estimates. The utility of the method is demonstrated for two separate forms of MOOTW. It is applied to humanitarian military intervention by estimating a force for a hypothetical EU intervention in Libya. It is then applied to noncombatant evacuation operations by estimating forces required for the American evacuation of Afghanistan in August 2021, showing its ability to mimic real-world decisionmaking. The method produced estimates that were more accurate than those produced by force ratio methods, and in both cases the method and the campaign analysis it enabled are able to answer important, policy-relevant questions.
dc.publisherMassachusetts Institute of Technology
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.titleA Mixed-Methods Approach to Force Estimation in Military Operations Other Than War
dc.typeThesis
dc.description.degreeS.M.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Political Science
dc.identifier.orcid0000-0002-5160-7684
mit.thesis.degreeMaster
thesis.degree.nameMaster of Science in Political Science


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