Influence of Factor-Magnitude on Occupational Stress Among Agricultural Research Sector Employees in Kenya
Bibliographic record
Abstract
Job dissatisfaction is inevitable in any work environment. The present study explored influence of factor-magnitude on occupational stress among agricultural research sector employees in Kenya. The study was carried out during the restructuring period of the agricultural research institutes in Kenya between 2013 and 2016. The restructuring resulted in the formation of the Agricultural and Livestock Research Organization through the dissolution of four agricultural research institutes and merger of their operations and functions. The former institutes were: Coffee Research Foundation, Kenya Agricultural Research Institute, Kenya Sugar Research Foundation, and Tea Research Foundation. The 2922 employees of the organization were disillusioned during the four years of restructuring due to the loss of upkeep allowances among other benefits. A structured questionnaire was administered to 352 randomly selected employees in a survey carried out in 2016–2017. The study found that poor working conditions, effort-reward imbalance, job psychological distress, and lack of work motivation had significant (p < 0.05) effects on occupational stress. It was concluded that the on-going structural and remuneration changes would result in higher levels of job satisfaction and reduction in occupational stress among employees.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".