Stakeholder participation in project performance: Insights from Uganda’s Youth Livelihood Programme
Bibliographic record
Abstract
Background: Community participation is increasingly highlighted in policy discussions as essential for the effectiveness and sustainability of government-led socio-economic initiatives. However, in many developing countries, including Uganda, communities are often excluded from key phases such as planning, budgeting and implementation, leading to diminished project ownership and poor outcomes. Aim: The study aims to evaluate how stakeholder participation influences the success of the Youth Livelihood Programme (YLP), with a specific focus on participatory planning, budgeting and implementation. Setting: The research was conducted in Luuka District, Uganda, where the YLP has faced various challenges since its launch in 2013. Methods: A descriptive research design was employed, integrating both qualitative and quantitative data. Data collection included self-administered questionnaires, semi-structured interviews and a review of relevant literature to capture stakeholder perspectives on programme performance. Results: The findings indicate that stakeholder participation in planning and budgeting had minimal impact on overall programme success. In contrast, active participation during the implementation phase positively influenced project outcomes, highlighting the significance of community involvement in ensuring effective delivery. Conclusion: The study concludes that while there is a need to improve participatory practices in planning and budgeting, fostering active community involvement in the implementation phase is crucial for achieving better project outcomes and sustainability. Contribution: This study provides empirical evidence on the role of stakeholder participation in enhancing the performance of development programmes. It underscores the need for policy reforms to strengthen participatory mechanisms in government initiatives, offering practical insights for improving programme sustainability in similar socio-economic contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".