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Polemology --- History of North America --- anno 2000-2009 --- United States of America

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This report investigates humanitarian and stabilization needs in Iraq, through a case study of Mosul. and offers recommendations for actions for stabilization after liberation from ISIS. The research team examined humanitarian needs, security implications, infrastructure and services, and governance and reconciliation. All of these activities will affect the immediate stabilization of Iraq and Mosul more specifically, including whether civilians can return home.

Postwar reconstruction --- Nation-building --- Humanitarian assistance, American --- Infrastructure (Economics) --- Economic stabilization --- Internal security --- History --- IS (Organization) --- Iraq --- Politics and government

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How can the success (or failure) of Army special operations missions be assessed? The authors develop a methodology for doing so that relies on operational, intelligence, and ambient (publicly available) data, since operational level special operations commands often lack robust staff and resources to generate assessment-specific information. The method assesses the plan's lines of effort and their objectives, develops relevant measures of effectiveness and indicators, and gathers appropriate qualitative and quantitative data. The resulting analysis is presented to the appropriate commander, who can then use the information to adjust lines of effort or activities and other elements. The seven-step process is illustrated through a fictional scenario. Implementation will include incorporating the approach into doctrine and training and standing up an assessment cell. The cell requires access to data streams and appropriate analytic platforms and reachback support.

Special operations (Military science) --- Special forces (Military science) --- Evaluation.

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"This report contributes to the ongoing debate about the lessons from the past 13 years of war and the requirements for addressing future conflicts. It addresses a particular disconnect in the current debate on the future of national security strategy and the role of landpower caused by an inadequate examination of the national level of strategy made by the U.S. government. The disconnect exists because there has been no systematic effort to collect and analyze insights from those who have been actively engaged in making policy and strategy from 2001 to 2014. A RAND Arroyo Center workshop provided a mechanism for eliciting insights from policymakers and academic experts involved in the formation of national-level strategy and its implementation over the past 13 years. This study analyzes and develops those insights in the context of the debate on future national security strategy. It applies those insights to the future operating environment, which will include irregular and hybrid threats, and identifies critical requirements for land forces and special operations forces to operate successfully in conjunction with other joint, interagency, and multinational partners."--Publisher's website.

Strategy --- National security --- Afghan War, 2001 --- -Iraq War, 2003-2011 --- Integrated operations (Military science) --- Irregular warfare --- Military Science - General --- Military & Naval Science --- Law, Politics & Government --- Decision making --- Evaluation --- Forecasting --- IW (Irregular warfare) --- Unconventional warfare --- Combined integrated operations (Military science) --- Multinational integrated operations (Military science) --- Anglo-American Invasion of Iraq, 2003-2011 --- Dawn, Operation New, 2010-2011 --- Gulf War II, 2003-2011 --- Iraqi Freedom, Operation, 2003-2010 --- New Dawn, Operation, 2010-2011 --- Operation Iraqi Freedom, 2003-2010 --- Operation New Dawn, 2010-2011 --- Operation Telic, 2003-2011 --- Persian Gulf War, 2003-2011 --- Telic, Operation, 2003-2011 --- National security policy --- NSP (National security policy) --- Security policy, National --- Military strategy --- Government policy --- War --- Guerrilla warfare --- Civil-military relations --- Military art and science --- War on Terrorism, 2001-2009 --- Operation Enduring Freedom, 2001 --- -War on Terrorism, 2001-2009 --- Economic policy --- International relations --- Military policy --- Military doctrine --- -Operation Enduring Freedom, 2001 --- Afghan War, 2001-2021 --- Iraq War, 2003-2011 --- United States --- Evaluation. --- Military policy. --- Armed Forces --- Stability operations. --- Strategic aspects. --- JIIM (joint, interagency, integovernmental and multinational) --- lessons learned --- ABŞ --- ABSh --- Ameerika Ühendriigid --- America (Republic) --- Amerika Birlăshmish Shtatlary --- Amerika Birlăşmi Ştatları --- Amerika Birlăşmiş Ştatları --- Amerika ka Kelenyalen Jamanaw --- Amerika Qūrama Shtattary --- Amerika Qŭshma Shtatlari --- Amerika Qushma Shtattary --- Amerika (Republic) --- Amerikai Egyesült Államok --- Amerikanʹ Veĭtʹsėndi︠a︡vks Shtattnė --- Amerikări Pĕrleshu̇llĕ Shtatsem --- Amerikas Forenede Stater --- Amerikayi Miatsʻyal Nahangner --- Ameriketako Estatu Batuak --- Amirika Carékat --- AQSh --- Ar. ha-B. --- Arhab --- Artsot ha-Berit --- Artzois Ha'bris --- Bí-kok --- Ē.P.A. --- EE.UU. --- Egyesült Államok --- ĒPA --- Estados Unidos --- Estados Unidos da América do Norte --- Estados Unidos de América --- Estaos Xuníos --- Estaos Xuníos d'América --- Estatos Unitos --- Estatos Unitos d'America --- Estats Units d'Amèrica --- Ètats-Unis d'Amèrica --- États-Unis d'Amérique --- Fareyniḳṭe Shṭaṭn --- Feriene Steaten --- Feriene Steaten fan Amearika --- Forente stater --- FS --- Hēnomenai Politeiai Amerikēs --- Hēnōmenes Politeies tēs Amerikēs --- Hiwsisayin Amerikayi Miatsʻeal Tērutʻiwnkʻ --- Istadus Unidus --- Jungtinės Amerikos valstybės --- Mei guo --- Mei-kuo --- Meiguo --- Mî-koet --- Miatsʻyal Nahangner --- Miguk --- Na Stàitean Aonaichte --- NSA --- S.U.A. --- SAD --- Saharat ʻAmērikā --- SASht --- Severo-Amerikanskie Shtaty --- Severo-Amerikanskie Soedinennye Shtaty --- Si︠e︡vero-Amerikanskīe Soedinennye Shtaty --- Sjedinjene Američke Države --- Soedinennye Shtaty Ameriki --- Soedinennye Shtaty Severnoĭ Ameriki --- Soedinennye Shtaty Si︠e︡vernoĭ Ameriki --- Spojené obce severoamerické --- Spojené staty americké --- SShA --- Stadoù-Unanet Amerika --- Stáit Aontaithe Mheiriceá --- Stany Zjednoczone --- Stati Uniti --- Stati Uniti d'America --- Stâts Unîts --- Stâts Unîts di Americhe --- Steatyn Unnaneysit --- Steatyn Unnaneysit America --- SUA (Stati Uniti d'America) --- Sŭedineni amerikanski shtati --- Sŭedinenite shtati --- Tetã peteĩ reko Amérikagua --- U.S. --- U.S.A. --- United States of America --- Unol Daleithiau --- Unol Daleithiau America --- Unuiĝintaj Ŝtatoj de Ameriko --- US --- USA --- Usono --- Vaeinigte Staatn --- Vaeinigte Staatn vo Amerika --- Vereinigte Staaten --- Vereinigte Staaten von Amerika --- Verenigde State van Amerika --- Verenigde Staten --- VS --- VSA --- Wááshindoon Bikéyah Ałhidadiidzooígíí --- Wilāyāt al-Muttaḥidah --- Wilāyāt al-Muttaḥidah al-Amirīkīyah --- Wilāyāt al-Muttaḥidah al-Amrīkīyah --- Yhdysvallat --- Yunaeted Stet --- Yunaeted Stet blong Amerika --- ZDA --- Združene države Amerike --- Zʹi︠e︡dnani Derz︠h︡avy Ameryky --- Zjadnośone staty Ameriki --- Zluchanyi︠a︡ Shtaty Ameryki --- Zlucheni Derz︠h︡avy --- ZSA --- Η.Π.Α. --- Ηνωμένες Πολιτείες της Αμερικής --- Америка (Republic) --- Американь Вейтьсэндявкс Штаттнэ --- Америкӑри Пӗрлешӳллӗ Штатсем --- САЩ --- Съединените щати --- Злучаныя Штаты Амерыкі --- ولايات المتحدة --- ولايات المتّحدة الأمريكيّة --- ولايات المتحدة الامريكية --- 미국 --- Stabilization operations --- États-Unis --- É.-U. --- ÉU --- Iraq War, 2003-2011. --- Irregular warfare. --- Forecasting.

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The authors describe an approach for leveraging machine learning to support assessment of military operations. They demonstrate how machine learning can be used to rapidly and systematically extract assessment-relevant insights from unstructured text available in intelligence reporting, operational reporting, and traditional and social media. These data, already collected by operational-level headquarters, are often the best available source of information about the local population and enemy and partner forces but are rarely included in assessment because they are not structured in a way that is easily amenable to analysis. The machine learning approach described in this report helps overcome this challenge. The approach described in this report, which the authors illustrate using the recently concluded campaign against the Lord's Resistance Army, enables assessment teams to provide commanders with near-real-time insights about a campaign that are objective and statistically relevant. This machine learning approach may be particularly beneficial in campaigns with limited or no assessment-specific data, common in campaigns with limited resources or in denied areas. This application of machine learning should be feasible for most assessment teams and can be implemented with publicly and freely available machine learning tools pre-authorized for use on U.S. Department of Defense systems.