Assessment of Employee Well-Being on Organisational Effectiveness & Productivity: A Literature Review
Bibliographic record
Abstract
This paper examines the various and complex aspects of employee well-being, including global and individual perspectives. The study examines the pivotal role of leadership, organizational culture, job satisfaction, job quality, age and gender dynamics, and family-friendly practices in shaping employee well-being. Through a synthesis of existing research, key findings emerge, highlighting the significance of engaged leadership in promoting employee performance and well-being. Additionally, the impact of organizational justice and supportive work environments on employee perceptions of fairness and well-being is discussed. Furthermore, the relationship between job satisfaction, job quality, and employee well-being is explored, emphasizing the importance of addressing diverse employee needs. The study also delves into age and gender differences in well-being, as well as the influence of family-friendly practices on reducing work-life conflict. Overall, this literature review provides valuable insights for organizations seeking to prioritize employee well-being as a strategic imperative in today's dynamic business landscape, ultimately contributing to enhanced organizational performance and success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".