Repository logo
Communities & Collections
All of UCUDIR
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Leonard Akoch"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • No Thumbnail Available
    Item
    Predicting employment outcomes for youth with disabilities in economic empowerment programs: a machine learning approach
    (Uganda Christian University, 2026-06-12) Leonard Akoch
    Youth with disabilities face significant barriers to employment, including discrimination, limited access to education, and inaccessible workplaces which contribute to high unemployment rates and social exclusion. To improve the effectiveness of economic empowerment programs for this demographic, this study developed a machine learning model to predict employment outcomes for youth with disabilities. Drawing from data of 895 youth with disabilities from the Bunyoro subregion of Uganda who participated in economic empowerment programs, encompassing demographic data, disability types, intervention details, and employment status at follow‐up, we trained and evaluated several machine learning models. Among these were ensemble methods such as Random Forest, XGBoost, Gradient Boosting, and Stacking Ensemble. The Stacking Ensemble achieved the best performance with an accuracy of 97.21%, a precision of 92.73%, a recall of 98.08%, and an F1‐score of 95.22% in predicting improved employment status. The key factors driving employment success were soft skills training, the provision of start‐up kits, and the duration of the interventions. This research addresses the critical need to improve the effectiveness of economic empowerment initiatives developed to support youth with disabilities. The findings can inform other programs with similar contexts, contributing to broader development efforts and potentially inspiring the adoption of predictive modeling in other social programs targeting marginalized groups.

UCUDIR copyright © 2002-2026 UCU Library

  • Privacy policy
  • End User Agreement
  • Send Feedback