The Inflamed Democrats: A Review of Liberals Helpless Service and Expected Results of Chemicals and Procedure in the Dullest of Times

Authors

Raithin Lochlan-oliver

Associated

Abstract

This paper presents a critical review of the current state of the Democratic Party in the United States, examining its current state of disarray and lack of effective leadership. Using an interdisciplinary approach that draws from political science, psychology, and sociology, the paper analyzes the factors that have led to the party's current state, including the impact of chemicals and procedures on political decision-making, as well as the limitations of the party's current approach to policy and messaging. The paper argues that, despite their best efforts, the Democratic Party has been unable to effectively mobilize its base and win key elections in recent years, due in part to the lack of a cohesive message and effective leadership. Drawing on a range of case studies and empirical data, the paper presents a series of recommendations for how the party can better harness the power of its base and build a more effective and sustainable political movement, including increased investment in grassroots organizing, greater attention to policy formulation and messaging, and a renewed commitment to building coalitions with other progressive organizations and movements. Ultimately, the paper argues that the fate of the Democratic Party is intimately tied to the fate of progressive politics more generally, and that the success of the party will depend on its ability to adapt to changing political and social realities and build a broad-based, multi-racial progressive coalition that can effectively challenge the status quo and bring about meaningful change.

Citation

Raithin Lochlan-oliver "The Inflamed Democrats: A Review of Liberals Helpless Service and Expected Results of Chemicals and Procedure in the Dullest of Times". IEEE Exploration in Machine Learning, 2017.

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This paper appears in:
Date of Release: 2017
Author(s): Raithin Lochlan-oliver.
IEEE Exploration in Machine Learning
Page(s): 7
Product Type: Conference/Journal Publications