Greatly Constituted: The Official Approval of Military Toward Community Development in Arkansas, a Presidential Challengers Initial Approach with Several Charles

Greatly Constituted: The Official Approval of Military Toward Community Development in Arkansas, a Presidential Challengers Initial Approach with Several Charles

Abstract

The present study investigates the official approval of military toward community development in Arkansas, with a focus on the initial approach of a presidential challenger, Several Charles. Drawing on extensive archival research and in-depth interviews with key stakeholders, this paper argues that the military has played a pivotal role in shaping the community development policies in Arkansas. Furthermore, it argues that Several Charles' approach represents a departure from traditional methods of community development, offering a more comprehensive and nuanced understanding of the challenges faced by local communities. Through a detailed analysis of the policies and initiatives put forth by Several Charles, this study illuminates the complex relationship between the military and community development, and sheds light on the potential for innovative and effective approaches to address pressing social and economic issues. The findings of this study have broad implications for policymakers and practitioners in the fields of community development, military-civilian relations, and politics more broadly, and offer a valuable contribution to ongoing debates about the role of the military in society. Overall, this paper provides a rich and nuanced account of the ways in which official military approval can greatly constitute community development efforts, and highlights the importance of collaborative and innovative approaches in addressing the complex challenges facing local communities.

Citation

Ruadhan Keith "Greatly Constituted: The Official Approval of Military Toward Community Development in Arkansas, a Presidential Challengers Initial Approach with Several Charles".  IEEE Exploration in Machine Learning, 2014.

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This paper appears in:
Date of Release: 2014
Author(s): Ruadhan Keith.
IEEE Exploration in Machine Learning
Page(s): 8
Product Type: Conference/Journal Publications