Do values reflect what is important? Exploring the nexus between work values, work engagement and job burnout
Bibliographic record
Abstract
Purpose Work values are a representation of people’s priorities as they reflect what is pertinent for them and what they want to accomplish. In light of this, the purpose of this study is to understand the priorities given to work values (extrinsic and intrinsic) by employees and also to explore whether these work values vary with the levels of work engagement and job burnout. Design/methodology/approach The study was based on the survey responses of 386 officers working in Indian manufacturing organisations engaged in different areas. Findings The findings reveal that security officers give much priority to extrinsic work values than intrinsic work values (IWVs). Moreover, IWVs vary with different levels of work engagement along with job burnout. The security officers belonging to the engaged group differ significantly with those belonging to the job burnout group in terms of IWVs. Moreover, work values also have a negative correlation with job burnout and a positive correlation with work engagement. Originality/value This study explores the variation in work values of security officers working in Indian manufacturing organisations with changes in levels of job burnout and work engagement, which is a novel contribution in the field. The findings also advocate that it is crucial for human resource managers, supervisors and key people in organisations to find out employees showing early signs of job burnout (exhaustion or disengagement) or early stages of strain and frustration as the priorities of work values of the employees are affected by these parameters. Such identified employees should be provided with required managerial support and necessary work resources immediately.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".