Relationship Between Job Satisfaction and Employee Productivity in Hybrid Work Environments at Jhpiego Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As work extends beyond traditional office walls, understanding what sustains employee motivation and productivity becomes increasingly important. This study examines the relationship between job satisfaction and employee productivity in hybrid work environments, focusing on Jhpiego, a non-profit health organisation in Kenya. Hybrid work arrangements are now central to modern workplaces, making it critical to understand their impact for advancing the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 3 on Good Health and Well-being and SDG 8 on Decent Work and Economic Growth. Using a correlational design grounded in Herzberg’s Two-Factor Theory and the Job Characteristics Model, this study employed a census approach. Data was collected through a structured, self-administered online questionnaire from all 106 employees, including 90 full-time staff and 16 team leaders, at Jhpiego Kenya. The findings reveal that higher job satisfaction is strongly associated with greater employee productivity (r = 0.711, p < 0.01), underscoring the importance of autonomy, supportive policies, and clear communication in sustaining productivity. These results offer actionable insights for non-profit organisations seeking to optimise hybrid work models and contribute to global development goals. The research provides insights that support evidence-based decision-making for a wide range of stakeholders, including organisational leaders, human resource practitioners, employees, policymakers, and scholars, on the importance of fostering more adaptive, productive, and supportive workplaces in the evolving landscape of hybrid and flexible work.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it