Bibliographic record
Abstract
Purpose The purpose of this article is to explore the interrelationship between workplace stress, coping and resiliency and their influence on employee health and productivity. Design/methodology/approach This general review includes an examination of selected theoretical models within the areas of stress, coping and resiliency. In addition, a conceptual framework is presented which emphasizes the role that personality characteristics and coping strategies play in impacting employees' overall health and productivity within the workplace. Findings Through this general review, there is a recognition of the importance of both personality characteristics and coping strategies and their associated influence on employee health and productivity – specifically within Civil Service work settings. Practical implications Managers, executives and human resource management practitioners are presented with proposed strategies as a means of examining coping, resiliency and workplace stress within Civil Service work environments. Originality/value This article offers readers further insights into understanding why some employees are more or less resilient, given the same stressful situation. In today's Civil Service work environment, continually shifting performance expectations and media/public scrutiny are just two of the features common to working for government agencies. Therefore, the issue of understanding and building resilient Civil Service workforces that are able to handle the multitude of unique demands and constraints placed on them seems not only intriguing, but necessary.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".