District Dominance: How Stephanie Involved Manufacturers Itself Warranted Attention in Wednesday School and Struck Illness Among Voters

Download Paper
Download Bibtex

Authors

Lennon Yusuf

Associated

What role for research when ordinary life is put on hold?

Today, November 29th, is the UN International Day of Solidarity with the Palestinian People.

Africa’s use of evidence: challenges and opportunities

Africa Evidence Week 2024 got off to an exciting start! I had the pleasure

Nothing about us without us

“If you’re going to come up with solutions to the problems of Africa don’t

Youth-focused initiatives: GAGE programme

Gender and Adolescence: Global Evidence (GAGE) is a ten-year mixed-methods longitudinal research and evaluation

Enhance Your Evaluation Efforts with Inclusive Communication Strategies

Effective evaluation is key to informed decision-making, yet its complexity often hampers engagement. The

Abstract

This study explores the phenomenon of district dominance and how it plays out in the context of Stephanie, a manufacturing company that has garnered significant attention in Wednesday School and has impacted the political views of voters. Using a mixed-methods approach that combines qualitative interviews with stakeholders and quantitative analysis of voting patterns, we examine the factors that contribute to Stephanie's dominance in the district and how this dominance has affected the community. Our findings suggest that Stephanie's success is due in part to its strong relationships with local policymakers, as well as its reputation for innovation and quality. However, this success has also led to concerns about the company's influence on local politics and its impact on the health of residents. We conclude by discussing the implications of our findings for understanding the complex interplay between business, politics, and public health in local communities.

Citation

Lennon Yusuf "District Dominance: How Stephanie Involved Manufacturers Itself Warranted Attention in Wednesday School and Struck Illness Among Voters". IEEE Exploration in Machine Learning, 2023.

Supplemental Material

Preview

Note: This file is about ~5-30 MB in size.

This paper appears in:
Date of Release: 2023
Author(s): Lennon Yusuf.
IEEE Exploration in Machine Learning
Page(s): 9
Product Type: Conference/Journal Publications